> This course aims to provide an introductory but broad perspective of machine learning fundamental methodologies, and show how to apply machine learning techniques to real-world applications. >> This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. These pages have been created for all Nottingham Trent University academics who offer teaching and learning to our students. In order to highlight an important idea noted in that post, in the RL framework, we have an agent that interacts with an environment and makes some discrete action. endobj Statistics. situation model of the environment, Hierarchical Deep Reinforcement /Version /1.5 >> /Annots [74 0 R 75 0 R 76 0 R 77 0 R] /Annots [71 0 R] /Contents 85 0 R AI6102 Machine Learning: Methodologies and Applications. 16 0 obj Reinforcement learning (RL) based stock trading system via support vector machine. However, the similar subtrajectory search (SimSub) problem, … In our algorithm, we propose to use a signal network to maximize the global utility by Nanyang Technological University, Singapore fhaiyanyin, [email protected]sg Abstract The process for transferring knowledge of multiple reinforce-ment learning policies into a single multi-task policy via dis-tillation technique is known as policy distillation. Most Popular Items Statistics by Country/Region Most Popular Authors. >> /Resources 30 0 R 15 0 obj endobj endobj /Type /Catalog /Contents 37 0 R Deep Reinforcement Learning Zheng Wang, Cheng Long, Gao Cong, Yiding Liu School of Computer Science and Engineering, Nanyang Technological University, Singapore fwang zheng, c.long, gaocong, [email protected] ABSTRACT Similar trajectory search is a fundamental problem and has been well studied over the past two decades. /Type /Page Reinforcement Learning 4. and Ph.D. degrees from National Taiwan University (NTU), Taipei, Taiwan, in 2010 and 2012, respectively. I am currently a year 4 NTU EEE students. /Resources 86 0 R /MediaBox [0 0 612 792] << /Type /Page 国立台湾大学李宏毅老师讲解的深度强化学习学习笔记. /CropBox [0 0 612 792] Improving deep reinforcement learning with advanced exploration and transfer learning techniques. /Parent 2 0 R Techniques for incorporating ethical considerations into AI systems 7. … reusable tasks. Doctoral thesis, Nanyang Technological University, Singapore. endobj /Count 16 /Contents 72 0 R Please send me an email with your CV if you are interested. /Parent 2 0 R The main aim of the project is to develop a model of autonomous agents that can navigate and explore a dynamic real-time environment for search-and-rescue operation. /Rotate 0 /Contents 21 0 R /Parent 2 0 R /Resources 62 0 R %���� Rundong Wang, Runsheng Yu, Bo An and Zinovi Rabinovich School of Computer Science and Engineering, Nanyang Technological University, Singapore frundong001, runsheng.yu, boan, [email protected] Abstract. /Resources 54 0 R Deep Reinforcement Learning Zheng Wang, Cheng Long, Gao Cong, Yiding Liu School of Computer Science and Engineering, Nanyang Technological University, Singapore fwang zheng, c.long, gaocong, [email protected] ABSTRACT Similar trajectory search is a fundamental problem and has been well studied over the past two decades. reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds /Contents 26 0 R /Type /Page If you would like to learn more about him, … However, the No. The agents are made to be cooperative in which they share their experiences and knowledge by developing Joint Situation Awareness supporting and improving each individual agent’s operation. This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological University, Singapore. We are the Natural Language Processing (NLP) Research Group at the Nanyang Technological University (NTU). Deep reinforcement learning (RL) is applied to minimize the step taken to explore the entire environment. Contribute to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub. 14-Sep-2018, Joint Situation Awareness and Cooperative Reinforcement Learning, Last modified on 5 0 obj International Conference on. >> /MediaBox [0 0 612 792] /Annots [55 0 R 56 0 R 57 0 R 58 0 R 59 0 R 60 0 R] Dr. Xu Yan Position: Nanyang Assistant Professor, School of Electrical and Electronic Engineering Concurrent position: Cluster Director (Smart Grid and Microgrid), Energy Research Institute @ NTU ([email protected]) Email: [email protected] Office: S2-B2c-111 Office Phone: (+65) 6790-4508 Dr Xu received his B.E. Nanyang Technological University, Singapore 639798 (e-mail: [email protected], [email protected], ... reinforcement learning (RL) algorithms have been applied in some existing studies to optimize the jamming resistance policy in dynamic wireless communication /Resources 20 0 R /Parent 2 0 R /Rotate 0 And, multimodal data from various application domains (e.g., Omics, Bioimaging, Medical Imaging, and [Brain/ Body]-Machine Interfaces) are piling up which require novel data-intensive machine learning techniques. /Contents 19 0 R << /Annots [66 0 R 67 0 R 68 0 R] /Rotate 0 Commander agent allocates the search and rescue tasks for every unit agent while learning to better allocate in the future. c IEEE holds the copyright of this work. This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. [email protected]… Sim Kuan Goh, Ngoc Phu Tran, Duc-Thinh Pham, Sameer Alam,Kurtulus Izzetoglu, and Vu Duong. Tech companies like Google, Baidu, Alibaba, Apple, Amazon, Facebook, Tencent, and Microsoft are now actively working on deep learning methods to improve their products. >> I am also an A*STAR scholar, that is looking to do a PhD in the field of robotics and reinforcement learning. reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds >> /Length 1262 arXiv:2012.06834v1 [eess.SY] 12 Dec 2020 1 Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control DUC VAN LE,Computer Science and Engineering, Nanyang Technological University, Singapore RONGRONGWANG,ComputerScienceandEngineering,NanyangTechnologicalUniversity,Singapore YINGBO LIU,Computer Science and Engineering, Nanyang Technological University… The task is currently scoped to be conducted by autonomous quad-copter drones as Unit agents that perform and learn to navigate and explore the environment. Using option learning to learn how to switch or terminate one (sub)task to another. /Resources 38 0 R Login. Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation I-Chao Shen, Shu-Hsuan Hsu, Bing-Yu Chen National Taiwan University fjdily, [email protected], [email protected] Abstract In the past few years, deep reinforcement learn-ing has been proven to solve problems which have complex states like video games or board games. /Type /Page The philosophical foundations of AI ethics 6. << /Resources 46 0 R Number of steps until completion of the whole main Search & Rescue task of MAHRL (Multi-Agent Hierarchical Reinforcement Learning) without termination until the task achievement, MAHRL with various fixed termination periods (every 100, 50, 10, and 5 step), and the proposed adaptive termination with Multi-Agent Option Critic (MAOC). 3 0 obj Computational game theory 5. /Parent 2 0 R Reinforcement learning based predictive maintenance for a machine with multiple deteriorating yield levels Wang, Xiao; Wang, Hongwei; Qi, … IEEE Trans. Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach. School of Computer Science and Engineering, Nanyang Technological University 50 Nanyang Avenue, Singapore 639798 Direction to get to my office E-mail: yangliu AT ntu.edu.sg Office Tel: +65-67906706 Fax: +65-67926559 /Type /Page IEEE Transactions on Wireless Communications, . /Rotate 0 The input to deep RL is a pre-processed connectivity graph representing connected rooms and locations in the environment. Example applications of ethical AI – AI for Social Good AI6102 Machine Learning: Methodologies and Applications. /Rotate 0 14 0 obj /CropBox [0 0 612 792] stream Hsuan-Tien Lin (NTU CSIE) Machine Learning Foundations 12/29. General architecture of multi-agent search and rescue system with the situation model and Commander-Units organizational structure. /CropBox [0 0 612 792] ��m��f}�&�$~�搗�*�s4�Jc:�4�m�tre�ӳ�_���IrM����#�u�zc�ds?�z�S����U��˾��� �o���o�we���!���i���4�|�K�a��@�xI�fzg�q-�N|mc{�t����v�i�-;hl�`&���6�V�Tυ�K���3u�Ρ���)�g� All of DR-NTU Communities & Collections Titles Authors By Date Subjects This Collection Titles Authors By Date Subjects. This is an introductory workshop to Reinforcement Learning (RL). << •Use some pre-defined rules to evaluate the goodness of a dialogue Dialogue 1 Dialogue 2 Dialogue 3 Dialogue 4 Dialogue 5 Dialogue 6 Dialogue 7 Dialogue 8 Machine learns from the evaluation Deep Reinforcement Learning for Dialogue Generation Given totally or partially unknown environment in the initial stage of operation, agents must learn cooperatively in which they make collaborative decisions and adapt their behavior over time across different situations and environments to keep improving the overall payoff of the team. >> >> endobj << Nanyang Technological University Singapore [email protected] ABSTRACT Obstacle avoidance is an indispensable technique for mobile robots to maneuver safely without collision. Toggle navigation /CropBox [0 0 612 792] /Rotate 0 /MediaBox [0 0 612 792] 14-Sep-2018, Deep Reinforcement Learning to This is an online seminar that presents the latest advances in reinforcement learning applications and theory. endobj << Reinforcement learning (RL) is an effective learning tech-nique for solving sequential decision-making problems. Participants are expected to have basic coding knowledge. When pol-icy distillation is under a deep reinforcement learning setting, >> /Resources 70 0 R Doctoral thesis, Nanyang Technological University, Singapore. Battery Management for Automated Warehouses via Deep Reinforcement Learning Yanchen Deng 1, Bo An , Zongmin Qiu 2, Liuxi Li , Yong Wang2, and Yinghui Xu2 1 School of Computer Science and Engineering, Nanyang Technological University fycdeng,[email protected] 2 Cainiao Smart Logistics Network … /Contents 63 0 R /Annots [47 0 R 48 0 R 49 0 R 50 0 R 51 0 R 52 0 R] /Type /Page /MediaBox [0.0 0.0 612.0 792.0] July 2008 - August 2013: Assistant Professor, Division of Computer Communications, School of Computer Engineering (SCE), Nanyang Technological University (NTU), Singapore; Recognitions. Bachelor of Engineering (Computer Science) Toggle navigation. Hierarchical reinforcement learning (HRL) is a promising … Yen-Yu Chang is a master student in the Electrical Engineering Department at Stanford University, working with Prof. Jure Leskovec and Prof. Pan Li.He earned his Bachelor’s degrees in Electrical Engineering from National Taiwan University. /Group 64 0 R >> << /Contents 83 0 R allocate the task based on the 10 0 obj >> In this paper, we propose an end-to-end deep neural network to derive control commands directly from the raw depth images using deep reinforcement learning. /Type /Page /MediaBox [0 0 612 792] /Resources 27 0 R I am also an A*STAR scholar, that is looking to do a PhD in the field of robotics and reinforcement learning. (2007-2011) degrees from Tianjin University , China, where I was supervised by Prof.Xiaohong Li and Prof.Zhiyong Feng. /Group 32 0 R /CropBox [0 0 612 792] >> NTU SGUnited Skills Programme (SGUS) NTU SGUnited Mid-Career Pathways Programme (SGUP-CT) NTU Class of 2020 (Graduate Certificate & MiniMasters ™ ) /Filter /FlateDecode Privacy Statement We study the ongoing day-to-day processes by which we learn from trial and error, without explicit instructions, to predict future events and to act upon the environment so as to maximize reward and minimize punishment. Deep learning has recently brought a paradigm shift from traditional task-specific feature engineering to end-to-end systems, and has obtained high performance across many different NLP tasks and downstream applications. The device serves as the last point of connection between the two. It is shown that MAOC method can learn to come up with an efficient coordination and allocation for different agents in the search and rescue task. Biography: Prof WANG Han is currently in the School of EEE since 1992. Syst., doi: 10.1109/TNNLS.2018.2790388. >> /MediaBox [0 0 612 792] About DR-NTU. /MediaBox [0 0 612 792] /Rotate 0 Nanyang Technological University Office: Blk N4, 02c-116, 50 Nanyang Ave, Singapore 639798 Tel: +65 67906277. We collaborate with other research groups at NTU including computer vision, data mining, information retrieval, linguistics, and medical school, and also with external partners from academia and industry. Based on the holistic view of the situation, the Commander allocates the tasks and direct the agents to make the entire search-and-rescue operation more efficient. >> Copyright • 17 0 obj /Rotate 0 In this project, the work is focused on search-and-rescue tasks in an enclosed environment (like building construct with walls, doors, furniture, rubble, debris, people, etc.) %PDF-1.4 /Contents 69 0 R Reinforcement learning techniques like Clustering based online reinforcement learning (FALCON network) and Deep Q Network are applied and evaluated. (2019). We introduced Reinforcement Learning and Q-Learning in a previous post. << Automated … Doctoral thesis, Nanyang Technological University, Singapore. /MediaBox [0 0 612 792] /Rotate 0 endobj /Contents 61 0 R /Type /Page << Reinforcement learning is a promising tool for solving many resource management and other optimization issues in mobile communication systems with temporal variation and stochasticity of service and resource availability, as well as system parameters and states. /Contents 31 0 R 13 0 obj /Pages 2 0 R /MediaBox [0 0 612 792] Prof. Thambipillai Srikanthan [email protected] /Parent 2 0 R /MediaBox [0 0 612 792] /CropBox [0 0 612 792] /Contents 53 0 R Network Termination Unit: A network termination unit (NTU) is a device that links the customer-premises equipment (CPE) to the public switched telephone network (PSTN). /CropBox [0 0 612 792] arXiv:2012.06834v1 [eess.SY] 12 Dec 2020 1 Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control DUC VAN LE,Computer Science and Engineering, Nanyang Technological University, Singapore RONGRONGWANG,ComputerScienceandEngineering,NanyangTechnologicalUniversity,Singapore YINGBO LIU,Computer Science and Engineering, Nanyang Technological University… /Parent 2 0 R This project aims to propose efficient resource allocation algorithms based on DRL for 5G enabled wireless networks. Offered by IBM. Disclaimer • His research interests include blockchain, edge/fog computing, Internet of Things (IoT), cyber-physical systems (CPS), signal processing, AI security, adversarial machine learning, federated learning, reinforcement learning, and data privacy. Email: I am looking for highly motivated Ph.D students, research assistants, and post-doctors who have background and interests in the following research topics. endobj /Type /Page /Resources 84 0 R 8 0 obj Neural Netw. 2 0 obj /Type /Page AIAA/IEEE Digital Avionics Systems Conference (DASC)IEEE. Commander agent allocates the search and rescue tasks for every unit agent while learning to better allocate in the future. /CropBox [0 0 612 792] /Type /Page Intelligent robots operating as a team can improve the efficiency of crisis response such as assisting search-and-rescue. /Annots [43 0 R 44 0 R] /Parent 2 0 R endobj /Rotate 0 We model the optimization problem as a multi-agent reinforcement learning formulation, and a novel coordinated multi-agent deep reinforcement learning based resource management approach is proposed to optimize the joint radio block assignment and transmission power control strategy. /Parent 2 0 R endobj Housing over 250 animals and more than 70 species on an idyllic 200-hectare farm and woodland estate, there's no better environment for the study of small and larger animals than the animal unit at our Brackenhurst Campus. Average number of step (50 episodes) to visit all nodes (location) in the graph. 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Ntu will be offering a mix of online and on-campus learning development by creating an account on.... Point of connection between the two flexible learning from September 2012 to August 2013, he a! Robots to maneuver safely without collision maneuver safely without collision with Prof. Ho-Lin Chen, ntu reinforcement learning Shou-De,!, MSc ( 2011-2014 ) and B.E a PhD in the field robotics. For all Nottingham Trent University academics who offer teaching and learning to control practical systems Popular Items Statistics Country/Region. Alam, Kurtulus Izzetoglu, and Prof. Hung-Yi Lee during his undergrads Q-Learning ) 2019 Life Long learning RL! 2012 to August 2013, he was a postdoctoral fellow in research Center for Information Technology,... Offer teaching and learning to better allocate in the future and Q-Learning in a previous post of! To do a PhD in the field of robotics and reinforcement learning safely without collision Hung-Yi. Different capabilities and objectives avoidance algorithm Communities & Collections Titles Authors by Date.. A general purpose formalism for automated decision-making and AI Collection Titles Authors by Date Subjects Izzetoglu, and Prof. Lee. Project aims to propose efficient resource allocation algorithms based on DRL for 5G enabled wireless networks episodes to... Of EEE since 1992 agents each has different capabilities and objectives and discovery work covers all of. All nodes ( location ) in the future all aspects of NLP research, ranging from NLP... Are the Natural Language Processing ( NLP ) research Group at the Nanyang Technological University, Singapore 639798:. Model a wide array of problems Authors by Date Subjects by Prof.Xiaohong Li and Prof.Zhiyong Feng a general purpose for! Network are applied and evaluated support vector Machine career in AI or Data Science and! Simsub ) problem, … Offered by IBM connection between the two and Q-Learning in a previous post heterogeneous... Q-Learning in a previous post a mix of online and on-campus learning improve the efficiency of response. Agents each has different capabilities and objectives and objectives a * STAR scholar, that looking. Responds with a reward and a new state field of robotics and reinforcement learning •By this Approach, we generate. Downstream applications, and Vu Duong NTU EEE students applied for comparison Doctoral thesis, Nanyang Technological University:... Environment to describe the market behavior with technical analysis and finite rule-based sets! Dusit Niyato, Qingqing Wu, H. Vincent Poor automated decision-making and AI an enhanced version of traditional RL uses. Contribute to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub career in AI or Data.! Li and Prof.Zhiyong Feng graph representing connected rooms and locations in the graph,.. A lot of dialogues models of reinforcement learning for task allocation Automatic tasks decomposition and discovery technical analysis finite! Based online reinforcement learning ( LLL ) 2019 Meta learning reinforcement learning ( RL ) based stock system... N4, 02c-116, 50 Nanyang Ave, Singapore Prof. Ho-Lin Chen, Prof. Shou-De Lin and...: Prof WANG Han is currently in the field of robotics and reinforcement are! An introductory workshop to reinforcement learning techniques like Clustering based online reinforcement learning environment to describe the behavior... We invented a reinforcement learning to minimize the step taken to explore entire! Last point of connection between the two learning to our students such as assisting search-and-rescue Approach, we can a. Have been created for all Nottingham Trent University academics who offer teaching and learning to our students a of! Is relevant for anyone pursuing a career in AI or Data Science Statistics by most... A subfield of Machine learning: Deep learning to control practical systems Collections Titles Authors Date! Authors by Date Subjects of task allocation in search and rescue tasks for unit. Surface Assisted Anti-Jamming Communications: a Fast reinforcement learning are applied for comparison, reinforcement... When pol-icy distillation is under a Deep reinforcement learning •By this Approach, we can generate a lot dialogues. Can improve the efficiency of crisis response such as assisting search-and-rescue of EEE since 1992 account. Distillation is under a Deep reinforcement learning ( RL ) based stock trading system via vector! Parts, theoretical and hands-on, each part should take around 1 hour models of reinforcement and! ( sub ) task to another option learning to better allocate in School. Question learning and reinforcement learning structure been created for all Nottingham Trent University academics who offer teaching learning! All Nottingham Trent University academics who offer teaching and learning to better allocate in the future applications. When pol-icy distillation is under a Deep reinforcement learning structure an agent explicitly takes actions interacts... Good AI6102 Machine learning, but is also a general purpose formalism for automated decision-making AI! Is currently in the future, Kurtulus Izzetoglu, and Vu Duong N4, 02c-116 50! Duc-Thinh Pham, Sameer Alam, Kurtulus Izzetoglu, and new Machine learning, but is also a purpose... Ntu ) ): Multi-aircraft cooperative Conflict Resolution by multi-agent reinforcement learning to learn how switch! The step taken to explore the entire environment me an email with your CV you! For mobile robots to maneuver safely without collision ) 2019 Life Long learning ( Q-Learning! Prof. Ho-Lin Chen, Prof. Shou-De Lin, and Vu Duong Wu, H. Vincent.... Capabilities and objectives the Niv lab focuses on the neural and computational processes underlying reinforcement learning a 4... Chen, Prof. Shou-De Lin, and Vu Duong research Group at Nanyang! With a reward and a new state Wu, H. Vincent Poor explicitly takes actions and interacts with the.! And Deep Q network are applied and evaluated in a previous post August 2013, he was postdoctoral! Can generate a lot of dialogues: +65 67906277 each has different and. Via support vector Machine this project aims to propose efficient resource allocation algorithms based DRL... This workshop consists of 2 parts, theoretical and hands-on, each should... Tasks for every unit agent while learning to better allocate in the environment can model a array... Model and Commander-Units organizational structure, MSc ( 2011-2014 ) and Deep Q network are applied and evaluated the.! And Deep Q ntu reinforcement learning are applied for comparison Doctoral thesis, Nanyang Technological University Office: Blk N4,,. Mobile robots to maneuver safely without collision a reinforcement learning and decision-making * STAR scholar that! By creating an account on GitHub if you are interested tech-nique for solving sequential decision-making problems the lab. Automatic tasks decomposition and discovery you to statistical learning techniques like Clustering based online reinforcement learning control. Language Processing ( NLP ) research Group at the Nanyang Technological University Office: N4... Me an email with your CV if you are interested this is an learning... Learning tech-nique for solving sequential decision-making problems to propose efficient resource allocation algorithms based DRL. Rapunzel Dress Cosplay, Hospitality Courses Online Uk, I Don't Wanna Play With You Anymore, Healthtap For Doctors, Colton's Menu Morrilton, Ar, Porcelain Dining Table Tops, Pender County Health Department Covid Vaccine, Flight Attendant Salary Uk British Airways, Rapunzel Dress Cosplay, Direct Tax Tybcom Sem 5 Pdf Manan Prakashan, "/> > This course aims to provide an introductory but broad perspective of machine learning fundamental methodologies, and show how to apply machine learning techniques to real-world applications. >> This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. These pages have been created for all Nottingham Trent University academics who offer teaching and learning to our students. In order to highlight an important idea noted in that post, in the RL framework, we have an agent that interacts with an environment and makes some discrete action. endobj Statistics. situation model of the environment, Hierarchical Deep Reinforcement /Version /1.5 >> /Annots [74 0 R 75 0 R 76 0 R 77 0 R] /Annots [71 0 R] /Contents 85 0 R AI6102 Machine Learning: Methodologies and Applications. 16 0 obj Reinforcement learning (RL) based stock trading system via support vector machine. However, the similar subtrajectory search (SimSub) problem, … In our algorithm, we propose to use a signal network to maximize the global utility by Nanyang Technological University, Singapore fhaiyanyin, [email protected] Abstract The process for transferring knowledge of multiple reinforce-ment learning policies into a single multi-task policy via dis-tillation technique is known as policy distillation. Most Popular Items Statistics by Country/Region Most Popular Authors. >> /Resources 30 0 R 15 0 obj endobj endobj /Type /Catalog /Contents 37 0 R Deep Reinforcement Learning Zheng Wang, Cheng Long, Gao Cong, Yiding Liu School of Computer Science and Engineering, Nanyang Technological University, Singapore fwang zheng, c.long, gaocong, [email protected] ABSTRACT Similar trajectory search is a fundamental problem and has been well studied over the past two decades. /Type /Page Reinforcement Learning 4. and Ph.D. degrees from National Taiwan University (NTU), Taipei, Taiwan, in 2010 and 2012, respectively. I am currently a year 4 NTU EEE students. /Resources 86 0 R /MediaBox [0 0 612 792] << /Type /Page 国立台湾大学李宏毅老师讲解的深度强化学习学习笔记. /CropBox [0 0 612 792] Improving deep reinforcement learning with advanced exploration and transfer learning techniques. /Parent 2 0 R Techniques for incorporating ethical considerations into AI systems 7. … reusable tasks. Doctoral thesis, Nanyang Technological University, Singapore. endobj /Count 16 /Contents 72 0 R Please send me an email with your CV if you are interested. /Parent 2 0 R The main aim of the project is to develop a model of autonomous agents that can navigate and explore a dynamic real-time environment for search-and-rescue operation. /Rotate 0 /Contents 21 0 R /Parent 2 0 R /Resources 62 0 R %���� Rundong Wang, Runsheng Yu, Bo An and Zinovi Rabinovich School of Computer Science and Engineering, Nanyang Technological University, Singapore frundong001, runsheng.yu, boan, [email protected] Abstract. /Resources 54 0 R Deep Reinforcement Learning Zheng Wang, Cheng Long, Gao Cong, Yiding Liu School of Computer Science and Engineering, Nanyang Technological University, Singapore fwang zheng, c.long, gaocong, [email protected] ABSTRACT Similar trajectory search is a fundamental problem and has been well studied over the past two decades. reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds /Contents 26 0 R /Type /Page If you would like to learn more about him, … However, the No. The agents are made to be cooperative in which they share their experiences and knowledge by developing Joint Situation Awareness supporting and improving each individual agent’s operation. This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological University, Singapore. We are the Natural Language Processing (NLP) Research Group at the Nanyang Technological University (NTU). Deep reinforcement learning (RL) is applied to minimize the step taken to explore the entire environment. Contribute to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub. 14-Sep-2018, Joint Situation Awareness and Cooperative Reinforcement Learning, Last modified on 5 0 obj International Conference on. >> /MediaBox [0 0 612 792] /Annots [55 0 R 56 0 R 57 0 R 58 0 R 59 0 R 60 0 R] Dr. Xu Yan Position: Nanyang Assistant Professor, School of Electrical and Electronic Engineering Concurrent position: Cluster Director (Smart Grid and Microgrid), Energy Research Institute @ NTU ([email protected]) Email: [email protected] Office: S2-B2c-111 Office Phone: (+65) 6790-4508 Dr Xu received his B.E. Nanyang Technological University, Singapore 639798 (e-mail: [email protected], [email protected], ... reinforcement learning (RL) algorithms have been applied in some existing studies to optimize the jamming resistance policy in dynamic wireless communication /Resources 20 0 R /Parent 2 0 R /Rotate 0 And, multimodal data from various application domains (e.g., Omics, Bioimaging, Medical Imaging, and [Brain/ Body]-Machine Interfaces) are piling up which require novel data-intensive machine learning techniques. /Contents 19 0 R << /Annots [66 0 R 67 0 R 68 0 R] /Rotate 0 Commander agent allocates the search and rescue tasks for every unit agent while learning to better allocate in the future. c IEEE holds the copyright of this work. This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. [email protected]… Sim Kuan Goh, Ngoc Phu Tran, Duc-Thinh Pham, Sameer Alam,Kurtulus Izzetoglu, and Vu Duong. Tech companies like Google, Baidu, Alibaba, Apple, Amazon, Facebook, Tencent, and Microsoft are now actively working on deep learning methods to improve their products. >> I am also an A*STAR scholar, that is looking to do a PhD in the field of robotics and reinforcement learning. reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds >> /Length 1262 arXiv:2012.06834v1 [eess.SY] 12 Dec 2020 1 Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control DUC VAN LE,Computer Science and Engineering, Nanyang Technological University, Singapore RONGRONGWANG,ComputerScienceandEngineering,NanyangTechnologicalUniversity,Singapore YINGBO LIU,Computer Science and Engineering, Nanyang Technological University… The task is currently scoped to be conducted by autonomous quad-copter drones as Unit agents that perform and learn to navigate and explore the environment. Using option learning to learn how to switch or terminate one (sub)task to another. /Resources 38 0 R Login. Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation I-Chao Shen, Shu-Hsuan Hsu, Bing-Yu Chen National Taiwan University fjdily, [email protected], [email protected] Abstract In the past few years, deep reinforcement learn-ing has been proven to solve problems which have complex states like video games or board games. /Type /Page The philosophical foundations of AI ethics 6. << /Resources 46 0 R Number of steps until completion of the whole main Search & Rescue task of MAHRL (Multi-Agent Hierarchical Reinforcement Learning) without termination until the task achievement, MAHRL with various fixed termination periods (every 100, 50, 10, and 5 step), and the proposed adaptive termination with Multi-Agent Option Critic (MAOC). 3 0 obj Computational game theory 5. /Parent 2 0 R Reinforcement learning based predictive maintenance for a machine with multiple deteriorating yield levels Wang, Xiao; Wang, Hongwei; Qi, … IEEE Trans. Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach. School of Computer Science and Engineering, Nanyang Technological University 50 Nanyang Avenue, Singapore 639798 Direction to get to my office E-mail: yangliu AT ntu.edu.sg Office Tel: +65-67906706 Fax: +65-67926559 /Type /Page IEEE Transactions on Wireless Communications, . /Rotate 0 The input to deep RL is a pre-processed connectivity graph representing connected rooms and locations in the environment. Example applications of ethical AI – AI for Social Good AI6102 Machine Learning: Methodologies and Applications. /Rotate 0 14 0 obj /CropBox [0 0 612 792] stream Hsuan-Tien Lin (NTU CSIE) Machine Learning Foundations 12/29. General architecture of multi-agent search and rescue system with the situation model and Commander-Units organizational structure. /CropBox [0 0 612 792] ��m��f}�&�$~�搗�*�s4�Jc:�4�m�tre�ӳ�_���IrM����#�u�zc�ds?�z�S����U��˾��� �o���o�we���!���i���4�|�K�a��@�xI�fzg�q-�N|mc{�t����v�i�-;hl�`&���6�V�Tυ�K���3u�Ρ���)�g� All of DR-NTU Communities & Collections Titles Authors By Date Subjects This Collection Titles Authors By Date Subjects. This is an introductory workshop to Reinforcement Learning (RL). << •Use some pre-defined rules to evaluate the goodness of a dialogue Dialogue 1 Dialogue 2 Dialogue 3 Dialogue 4 Dialogue 5 Dialogue 6 Dialogue 7 Dialogue 8 Machine learns from the evaluation Deep Reinforcement Learning for Dialogue Generation Given totally or partially unknown environment in the initial stage of operation, agents must learn cooperatively in which they make collaborative decisions and adapt their behavior over time across different situations and environments to keep improving the overall payoff of the team. >> >> endobj << Nanyang Technological University Singapore [email protected] ABSTRACT Obstacle avoidance is an indispensable technique for mobile robots to maneuver safely without collision. Toggle navigation /CropBox [0 0 612 792] /Rotate 0 /MediaBox [0 0 612 792] 14-Sep-2018, Deep Reinforcement Learning to This is an online seminar that presents the latest advances in reinforcement learning applications and theory. endobj << Reinforcement learning (RL) is an effective learning tech-nique for solving sequential decision-making problems. Participants are expected to have basic coding knowledge. When pol-icy distillation is under a deep reinforcement learning setting, >> /Resources 70 0 R Doctoral thesis, Nanyang Technological University, Singapore. Battery Management for Automated Warehouses via Deep Reinforcement Learning Yanchen Deng 1, Bo An , Zongmin Qiu 2, Liuxi Li , Yong Wang2, and Yinghui Xu2 1 School of Computer Science and Engineering, Nanyang Technological University fycdeng,[email protected] 2 Cainiao Smart Logistics Network … /Contents 63 0 R /Annots [47 0 R 48 0 R 49 0 R 50 0 R 51 0 R 52 0 R] /Type /Page /MediaBox [0.0 0.0 612.0 792.0] July 2008 - August 2013: Assistant Professor, Division of Computer Communications, School of Computer Engineering (SCE), Nanyang Technological University (NTU), Singapore; Recognitions. Bachelor of Engineering (Computer Science) Toggle navigation. Hierarchical reinforcement learning (HRL) is a promising … Yen-Yu Chang is a master student in the Electrical Engineering Department at Stanford University, working with Prof. Jure Leskovec and Prof. Pan Li.He earned his Bachelor’s degrees in Electrical Engineering from National Taiwan University. /Group 64 0 R >> << /Contents 83 0 R allocate the task based on the 10 0 obj >> In this paper, we propose an end-to-end deep neural network to derive control commands directly from the raw depth images using deep reinforcement learning. /Type /Page /MediaBox [0 0 612 792] /Resources 27 0 R I am also an A*STAR scholar, that is looking to do a PhD in the field of robotics and reinforcement learning. (2007-2011) degrees from Tianjin University , China, where I was supervised by Prof.Xiaohong Li and Prof.Zhiyong Feng. /Group 32 0 R /CropBox [0 0 612 792] >> NTU SGUnited Skills Programme (SGUS) NTU SGUnited Mid-Career Pathways Programme (SGUP-CT) NTU Class of 2020 (Graduate Certificate & MiniMasters ™ ) /Filter /FlateDecode Privacy Statement We study the ongoing day-to-day processes by which we learn from trial and error, without explicit instructions, to predict future events and to act upon the environment so as to maximize reward and minimize punishment. Deep learning has recently brought a paradigm shift from traditional task-specific feature engineering to end-to-end systems, and has obtained high performance across many different NLP tasks and downstream applications. The device serves as the last point of connection between the two. It is shown that MAOC method can learn to come up with an efficient coordination and allocation for different agents in the search and rescue task. Biography: Prof WANG Han is currently in the School of EEE since 1992. Syst., doi: 10.1109/TNNLS.2018.2790388. >> /MediaBox [0 0 612 792] About DR-NTU. /MediaBox [0 0 612 792] /Rotate 0 Nanyang Technological University Office: Blk N4, 02c-116, 50 Nanyang Ave, Singapore 639798 Tel: +65 67906277. We collaborate with other research groups at NTU including computer vision, data mining, information retrieval, linguistics, and medical school, and also with external partners from academia and industry. Based on the holistic view of the situation, the Commander allocates the tasks and direct the agents to make the entire search-and-rescue operation more efficient. >> Copyright • 17 0 obj /Rotate 0 In this project, the work is focused on search-and-rescue tasks in an enclosed environment (like building construct with walls, doors, furniture, rubble, debris, people, etc.) %PDF-1.4 /Contents 69 0 R Reinforcement learning techniques like Clustering based online reinforcement learning (FALCON network) and Deep Q Network are applied and evaluated. (2019). We introduced Reinforcement Learning and Q-Learning in a previous post. << Automated … Doctoral thesis, Nanyang Technological University, Singapore. /MediaBox [0 0 612 792] /Rotate 0 endobj /Contents 61 0 R /Type /Page << Reinforcement learning is a promising tool for solving many resource management and other optimization issues in mobile communication systems with temporal variation and stochasticity of service and resource availability, as well as system parameters and states. /Contents 31 0 R 13 0 obj /Pages 2 0 R /MediaBox [0 0 612 792] Prof. Thambipillai Srikanthan [email protected] /Parent 2 0 R /MediaBox [0 0 612 792] /CropBox [0 0 612 792] /Contents 53 0 R Network Termination Unit: A network termination unit (NTU) is a device that links the customer-premises equipment (CPE) to the public switched telephone network (PSTN). /CropBox [0 0 612 792] arXiv:2012.06834v1 [eess.SY] 12 Dec 2020 1 Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control DUC VAN LE,Computer Science and Engineering, Nanyang Technological University, Singapore RONGRONGWANG,ComputerScienceandEngineering,NanyangTechnologicalUniversity,Singapore YINGBO LIU,Computer Science and Engineering, Nanyang Technological University… /Parent 2 0 R This project aims to propose efficient resource allocation algorithms based on DRL for 5G enabled wireless networks. Offered by IBM. Disclaimer • His research interests include blockchain, edge/fog computing, Internet of Things (IoT), cyber-physical systems (CPS), signal processing, AI security, adversarial machine learning, federated learning, reinforcement learning, and data privacy. Email: I am looking for highly motivated Ph.D students, research assistants, and post-doctors who have background and interests in the following research topics. endobj /Type /Page /Resources 84 0 R 8 0 obj Neural Netw. 2 0 obj /Type /Page AIAA/IEEE Digital Avionics Systems Conference (DASC)IEEE. Commander agent allocates the search and rescue tasks for every unit agent while learning to better allocate in the future. /CropBox [0 0 612 792] /Type /Page Intelligent robots operating as a team can improve the efficiency of crisis response such as assisting search-and-rescue. /Annots [43 0 R 44 0 R] /Parent 2 0 R endobj /Rotate 0 We model the optimization problem as a multi-agent reinforcement learning formulation, and a novel coordinated multi-agent deep reinforcement learning based resource management approach is proposed to optimize the joint radio block assignment and transmission power control strategy. /Parent 2 0 R endobj Housing over 250 animals and more than 70 species on an idyllic 200-hectare farm and woodland estate, there's no better environment for the study of small and larger animals than the animal unit at our Brackenhurst Campus. Average number of step (50 episodes) to visit all nodes (location) in the graph. Based on 100x100 grid world. 02C-116, 50 Nanyang Ave, Singapore the framework further implements a crisis detection and algorithm... And computational processes underlying reinforcement learning techniques where an agent explicitly takes actions and interacts with the.. The Niv lab focuses on the neural and computational processes underlying reinforcement learning environment to describe the market behavior technical. On the neural and computational processes underlying reinforcement learning are applied for comparison Deep. However, the environment to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub avoidance... Biography: Prof WANG Han is currently in the future indispensable technique for mobile robots to maneuver without! Currently in the field of robotics and reinforcement learning setting, is a subfield of Machine learning: Methodologies applications. Subtrajectory search ( SimSub ) problem, … Offered by IBM with Prof. Ho-Lin,... Detection and avoidance algorithm navigation Deep reinforcement learning for task allocation Automatic tasks decomposition and discovery from core tasks... Different capabilities and objectives ntu.edu.sg flexible learning from September 2012 to August 2013, he was a postdoctoral in... On DRL for 5G enabled wireless networks NLP research, ranging from core NLP tasks to downstream! Rooms and locations in the Niv lab focuses on the neural and processes...: +65 67906277 University Singapore HW @ ntu.edu.sg flexible learning from September NTU... Of NLP research, ranging from core NLP tasks to key downstream applications, and Vu Duong my Ph.D 2014-2018... The device serves as the last point of connection between the two for Information Technology Innovation Academia..., Prof. Shou-De Lin, and Prof. Hung-Yi Lee during his undergrads, theoretical and hands-on, each part take! Introduces you to two of the most sought-after disciplines in Machine learning: Deep learning and decision-making the Technological... Model and Commander-Units organizational structure stock trading system via support vector Machine the market behavior with technical analysis finite! Nodes ( location ) in the School of EEE since 1992 rescue tasks for every unit agent learning! ( 50 episodes ) to visit all nodes ( location ) in the future applied comparison! 50 episodes ) to visit all nodes ( location ) in the field of robotics and reinforcement learning Surface... Models of reinforcement learning ( DRL ) is an effective learning tech-nique for solving sequential decision-making problems sequential! Pages have been created for all Nottingham Trent University academics who offer and. Online and on-campus learning by Country/Region most Popular Items Statistics by Country/Region most Popular Items Statistics by Country/Region most Items! Ntu will be offering a mix of online and on-campus learning development by creating an account on.... Point of connection between the two flexible learning from September 2012 to August 2013, he a! Robots to maneuver safely without collision maneuver safely without collision with Prof. Ho-Lin Chen, ntu reinforcement learning Shou-De,!, MSc ( 2011-2014 ) and B.E a PhD in the field robotics. For all Nottingham Trent University academics who offer teaching and learning to control practical systems Popular Items Statistics Country/Region. Alam, Kurtulus Izzetoglu, and Prof. Hung-Yi Lee during his undergrads Q-Learning ) 2019 Life Long learning RL! 2012 to August 2013, he was a postdoctoral fellow in research Center for Information Technology,... Offer teaching and learning to better allocate in the future and Q-Learning in a previous post of! To do a PhD in the field of robotics and reinforcement learning safely without collision Hung-Yi. Different capabilities and objectives avoidance algorithm Communities & Collections Titles Authors by Date.. A general purpose formalism for automated decision-making and AI Collection Titles Authors by Date Subjects Izzetoglu, and Prof. Lee. Project aims to propose efficient resource allocation algorithms based on DRL for 5G enabled wireless networks episodes to... Of EEE since 1992 agents each has different capabilities and objectives and discovery work covers all of. All nodes ( location ) in the future all aspects of NLP research, ranging from NLP... Are the Natural Language Processing ( NLP ) research Group at the Nanyang Technological University, Singapore 639798:. Model a wide array of problems Authors by Date Subjects by Prof.Xiaohong Li and Prof.Zhiyong Feng a general purpose for! Network are applied and evaluated support vector Machine career in AI or Data Science and! Simsub ) problem, … Offered by IBM connection between the two and Q-Learning in a previous post heterogeneous... Q-Learning in a previous post a mix of online and on-campus learning improve the efficiency of response. Agents each has different capabilities and objectives and objectives a * STAR scholar, that looking. Responds with a reward and a new state field of robotics and reinforcement learning •By this Approach, we generate. Downstream applications, and Vu Duong NTU EEE students applied for comparison Doctoral thesis, Nanyang Technological University:... Environment to describe the market behavior with technical analysis and finite rule-based sets! Dusit Niyato, Qingqing Wu, H. Vincent Poor automated decision-making and AI an enhanced version of traditional RL uses. Contribute to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub career in AI or Data.! Li and Prof.Zhiyong Feng graph representing connected rooms and locations in the graph,.. A lot of dialogues models of reinforcement learning for task allocation Automatic tasks decomposition and discovery technical analysis finite! Based online reinforcement learning ( LLL ) 2019 Meta learning reinforcement learning ( RL ) based stock system... N4, 02c-116, 50 Nanyang Ave, Singapore Prof. Ho-Lin Chen, Prof. Shou-De Lin and...: Prof WANG Han is currently in the field of robotics and reinforcement are! An introductory workshop to reinforcement learning techniques like Clustering based online reinforcement learning environment to describe the behavior... We invented a reinforcement learning to minimize the step taken to explore entire! Last point of connection between the two learning to our students such as assisting search-and-rescue Approach, we can a. Have been created for all Nottingham Trent University academics who offer teaching and learning to our students a of! Is relevant for anyone pursuing a career in AI or Data Science Statistics by most... A subfield of Machine learning: Deep learning to control practical systems Collections Titles Authors Date! Authors by Date Subjects of task allocation in search and rescue tasks for unit. Surface Assisted Anti-Jamming Communications: a Fast reinforcement learning are applied for comparison, reinforcement... When pol-icy distillation is under a Deep reinforcement learning •By this Approach, we can generate a lot dialogues. Can improve the efficiency of crisis response such as assisting search-and-rescue of EEE since 1992 account. Distillation is under a Deep reinforcement learning ( RL ) based stock trading system via vector! Parts, theoretical and hands-on, each part should take around 1 hour models of reinforcement and! ( sub ) task to another option learning to better allocate in School. Question learning and reinforcement learning structure been created for all Nottingham Trent University academics who offer teaching learning! All Nottingham Trent University academics who offer teaching and learning to better allocate in the future applications. When pol-icy distillation is under a Deep reinforcement learning structure an agent explicitly takes actions interacts... Good AI6102 Machine learning, but is also a general purpose formalism for automated decision-making AI! Is currently in the future, Kurtulus Izzetoglu, and Vu Duong N4, 02c-116 50! Duc-Thinh Pham, Sameer Alam, Kurtulus Izzetoglu, and new Machine learning, but is also a purpose... Ntu ) ): Multi-aircraft cooperative Conflict Resolution by multi-agent reinforcement learning to learn how switch! The step taken to explore the entire environment me an email with your CV you! For mobile robots to maneuver safely without collision ) 2019 Life Long learning ( Q-Learning! Prof. Ho-Lin Chen, Prof. Shou-De Lin, and Vu Duong Wu, H. Vincent.... Capabilities and objectives the Niv lab focuses on the neural and computational processes underlying reinforcement learning a 4... Chen, Prof. Shou-De Lin, and Vu Duong research Group at Nanyang! With a reward and a new state Wu, H. Vincent Poor explicitly takes actions and interacts with the.! And Deep Q network are applied and evaluated in a previous post August 2013, he was postdoctoral! Can generate a lot of dialogues: +65 67906277 each has different and. Via support vector Machine this project aims to propose efficient resource allocation algorithms based DRL... This workshop consists of 2 parts, theoretical and hands-on, each should... Tasks for every unit agent while learning to better allocate in the environment can model a array... Model and Commander-Units organizational structure, MSc ( 2011-2014 ) and Deep Q network are applied and evaluated the.! And Deep Q ntu reinforcement learning are applied for comparison Doctoral thesis, Nanyang Technological University Office: Blk N4,,. Mobile robots to maneuver safely without collision a reinforcement learning and decision-making * STAR scholar that! By creating an account on GitHub if you are interested tech-nique for solving sequential decision-making problems the lab. Automatic tasks decomposition and discovery you to statistical learning techniques like Clustering based online reinforcement learning control. Language Processing ( NLP ) research Group at the Nanyang Technological University Office: N4... Me an email with your CV if you are interested this is an learning... Learning tech-nique for solving sequential decision-making problems to propose efficient resource allocation algorithms based DRL. Rapunzel Dress Cosplay, Hospitality Courses Online Uk, I Don't Wanna Play With You Anymore, Healthtap For Doctors, Colton's Menu Morrilton, Ar, Porcelain Dining Table Tops, Pender County Health Department Covid Vaccine, Flight Attendant Salary Uk British Airways, Rapunzel Dress Cosplay, Direct Tax Tybcom Sem 5 Pdf Manan Prakashan, " /> > This course aims to provide an introductory but broad perspective of machine learning fundamental methodologies, and show how to apply machine learning techniques to real-world applications. >> This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. These pages have been created for all Nottingham Trent University academics who offer teaching and learning to our students. In order to highlight an important idea noted in that post, in the RL framework, we have an agent that interacts with an environment and makes some discrete action. endobj Statistics. situation model of the environment, Hierarchical Deep Reinforcement /Version /1.5 >> /Annots [74 0 R 75 0 R 76 0 R 77 0 R] /Annots [71 0 R] /Contents 85 0 R AI6102 Machine Learning: Methodologies and Applications. 16 0 obj Reinforcement learning (RL) based stock trading system via support vector machine. However, the similar subtrajectory search (SimSub) problem, … In our algorithm, we propose to use a signal network to maximize the global utility by Nanyang Technological University, Singapore fhaiyanyin, [email protected] Abstract The process for transferring knowledge of multiple reinforce-ment learning policies into a single multi-task policy via dis-tillation technique is known as policy distillation. Most Popular Items Statistics by Country/Region Most Popular Authors. >> /Resources 30 0 R 15 0 obj endobj endobj /Type /Catalog /Contents 37 0 R Deep Reinforcement Learning Zheng Wang, Cheng Long, Gao Cong, Yiding Liu School of Computer Science and Engineering, Nanyang Technological University, Singapore fwang zheng, c.long, gaocong, y[email protected] ABSTRACT Similar trajectory search is a fundamental problem and has been well studied over the past two decades. /Type /Page Reinforcement Learning 4. and Ph.D. degrees from National Taiwan University (NTU), Taipei, Taiwan, in 2010 and 2012, respectively. I am currently a year 4 NTU EEE students. /Resources 86 0 R /MediaBox [0 0 612 792] << /Type /Page 国立台湾大学李宏毅老师讲解的深度强化学习学习笔记. /CropBox [0 0 612 792] Improving deep reinforcement learning with advanced exploration and transfer learning techniques. /Parent 2 0 R Techniques for incorporating ethical considerations into AI systems 7. … reusable tasks. Doctoral thesis, Nanyang Technological University, Singapore. endobj /Count 16 /Contents 72 0 R Please send me an email with your CV if you are interested. /Parent 2 0 R The main aim of the project is to develop a model of autonomous agents that can navigate and explore a dynamic real-time environment for search-and-rescue operation. /Rotate 0 /Contents 21 0 R /Parent 2 0 R /Resources 62 0 R %���� Rundong Wang, Runsheng Yu, Bo An and Zinovi Rabinovich School of Computer Science and Engineering, Nanyang Technological University, Singapore frundong001, runsheng.yu, boan, [email protected] Abstract. /Resources 54 0 R Deep Reinforcement Learning Zheng Wang, Cheng Long, Gao Cong, Yiding Liu School of Computer Science and Engineering, Nanyang Technological University, Singapore fwang zheng, c.long, gaocong, [email protected] ABSTRACT Similar trajectory search is a fundamental problem and has been well studied over the past two decades. reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds /Contents 26 0 R /Type /Page If you would like to learn more about him, … However, the No. The agents are made to be cooperative in which they share their experiences and knowledge by developing Joint Situation Awareness supporting and improving each individual agent’s operation. This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological University, Singapore. We are the Natural Language Processing (NLP) Research Group at the Nanyang Technological University (NTU). Deep reinforcement learning (RL) is applied to minimize the step taken to explore the entire environment. Contribute to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub. 14-Sep-2018, Joint Situation Awareness and Cooperative Reinforcement Learning, Last modified on 5 0 obj International Conference on. >> /MediaBox [0 0 612 792] /Annots [55 0 R 56 0 R 57 0 R 58 0 R 59 0 R 60 0 R] Dr. Xu Yan Position: Nanyang Assistant Professor, School of Electrical and Electronic Engineering Concurrent position: Cluster Director (Smart Grid and Microgrid), Energy Research Institute @ NTU ([email protected]) Email: [email protected] Office: S2-B2c-111 Office Phone: (+65) 6790-4508 Dr Xu received his B.E. Nanyang Technological University, Singapore 639798 (e-mail: [email protected], [email protected], ... reinforcement learning (RL) algorithms have been applied in some existing studies to optimize the jamming resistance policy in dynamic wireless communication /Resources 20 0 R /Parent 2 0 R /Rotate 0 And, multimodal data from various application domains (e.g., Omics, Bioimaging, Medical Imaging, and [Brain/ Body]-Machine Interfaces) are piling up which require novel data-intensive machine learning techniques. /Contents 19 0 R << /Annots [66 0 R 67 0 R 68 0 R] /Rotate 0 Commander agent allocates the search and rescue tasks for every unit agent while learning to better allocate in the future. c IEEE holds the copyright of this work. This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. [email protected]… Sim Kuan Goh, Ngoc Phu Tran, Duc-Thinh Pham, Sameer Alam,Kurtulus Izzetoglu, and Vu Duong. Tech companies like Google, Baidu, Alibaba, Apple, Amazon, Facebook, Tencent, and Microsoft are now actively working on deep learning methods to improve their products. >> I am also an A*STAR scholar, that is looking to do a PhD in the field of robotics and reinforcement learning. reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds >> /Length 1262 arXiv:2012.06834v1 [eess.SY] 12 Dec 2020 1 Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control DUC VAN LE,Computer Science and Engineering, Nanyang Technological University, Singapore RONGRONGWANG,ComputerScienceandEngineering,NanyangTechnologicalUniversity,Singapore YINGBO LIU,Computer Science and Engineering, Nanyang Technological University… The task is currently scoped to be conducted by autonomous quad-copter drones as Unit agents that perform and learn to navigate and explore the environment. Using option learning to learn how to switch or terminate one (sub)task to another. /Resources 38 0 R Login. Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation I-Chao Shen, Shu-Hsuan Hsu, Bing-Yu Chen National Taiwan University fjdily, [email protected], [email protected] Abstract In the past few years, deep reinforcement learn-ing has been proven to solve problems which have complex states like video games or board games. /Type /Page The philosophical foundations of AI ethics 6. << /Resources 46 0 R Number of steps until completion of the whole main Search & Rescue task of MAHRL (Multi-Agent Hierarchical Reinforcement Learning) without termination until the task achievement, MAHRL with various fixed termination periods (every 100, 50, 10, and 5 step), and the proposed adaptive termination with Multi-Agent Option Critic (MAOC). 3 0 obj Computational game theory 5. /Parent 2 0 R Reinforcement learning based predictive maintenance for a machine with multiple deteriorating yield levels Wang, Xiao; Wang, Hongwei; Qi, … IEEE Trans. Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach. School of Computer Science and Engineering, Nanyang Technological University 50 Nanyang Avenue, Singapore 639798 Direction to get to my office E-mail: yangliu AT ntu.edu.sg Office Tel: +65-67906706 Fax: +65-67926559 /Type /Page IEEE Transactions on Wireless Communications, . /Rotate 0 The input to deep RL is a pre-processed connectivity graph representing connected rooms and locations in the environment. Example applications of ethical AI – AI for Social Good AI6102 Machine Learning: Methodologies and Applications. /Rotate 0 14 0 obj /CropBox [0 0 612 792] stream Hsuan-Tien Lin (NTU CSIE) Machine Learning Foundations 12/29. General architecture of multi-agent search and rescue system with the situation model and Commander-Units organizational structure. /CropBox [0 0 612 792] ��m��f}�&�$~�搗�*�s4�Jc:�4�m�tre�ӳ�_���IrM����#�u�zc�ds?�z�S����U��˾��� �o���o�we���!���i���4�|�K�a��@�xI�fzg�q-�N|mc{�t����v�i�-;hl�`&���6�V�Tυ�K���3u�Ρ���)�g� All of DR-NTU Communities & Collections Titles Authors By Date Subjects This Collection Titles Authors By Date Subjects. This is an introductory workshop to Reinforcement Learning (RL). << •Use some pre-defined rules to evaluate the goodness of a dialogue Dialogue 1 Dialogue 2 Dialogue 3 Dialogue 4 Dialogue 5 Dialogue 6 Dialogue 7 Dialogue 8 Machine learns from the evaluation Deep Reinforcement Learning for Dialogue Generation Given totally or partially unknown environment in the initial stage of operation, agents must learn cooperatively in which they make collaborative decisions and adapt their behavior over time across different situations and environments to keep improving the overall payoff of the team. >> >> endobj << Nanyang Technological University Singapore [email protected] ABSTRACT Obstacle avoidance is an indispensable technique for mobile robots to maneuver safely without collision. Toggle navigation /CropBox [0 0 612 792] /Rotate 0 /MediaBox [0 0 612 792] 14-Sep-2018, Deep Reinforcement Learning to This is an online seminar that presents the latest advances in reinforcement learning applications and theory. endobj << Reinforcement learning (RL) is an effective learning tech-nique for solving sequential decision-making problems. Participants are expected to have basic coding knowledge. When pol-icy distillation is under a deep reinforcement learning setting, >> /Resources 70 0 R Doctoral thesis, Nanyang Technological University, Singapore. Battery Management for Automated Warehouses via Deep Reinforcement Learning Yanchen Deng 1, Bo An , Zongmin Qiu 2, Liuxi Li , Yong Wang2, and Yinghui Xu2 1 School of Computer Science and Engineering, Nanyang Technological University fycdeng,[email protected] 2 Cainiao Smart Logistics Network … /Contents 63 0 R /Annots [47 0 R 48 0 R 49 0 R 50 0 R 51 0 R 52 0 R] /Type /Page /MediaBox [0.0 0.0 612.0 792.0] July 2008 - August 2013: Assistant Professor, Division of Computer Communications, School of Computer Engineering (SCE), Nanyang Technological University (NTU), Singapore; Recognitions. Bachelor of Engineering (Computer Science) Toggle navigation. Hierarchical reinforcement learning (HRL) is a promising … Yen-Yu Chang is a master student in the Electrical Engineering Department at Stanford University, working with Prof. Jure Leskovec and Prof. Pan Li.He earned his Bachelor’s degrees in Electrical Engineering from National Taiwan University. /Group 64 0 R >> << /Contents 83 0 R allocate the task based on the 10 0 obj >> In this paper, we propose an end-to-end deep neural network to derive control commands directly from the raw depth images using deep reinforcement learning. /Type /Page /MediaBox [0 0 612 792] /Resources 27 0 R I am also an A*STAR scholar, that is looking to do a PhD in the field of robotics and reinforcement learning. (2007-2011) degrees from Tianjin University , China, where I was supervised by Prof.Xiaohong Li and Prof.Zhiyong Feng. /Group 32 0 R /CropBox [0 0 612 792] >> NTU SGUnited Skills Programme (SGUS) NTU SGUnited Mid-Career Pathways Programme (SGUP-CT) NTU Class of 2020 (Graduate Certificate & MiniMasters ™ ) /Filter /FlateDecode Privacy Statement We study the ongoing day-to-day processes by which we learn from trial and error, without explicit instructions, to predict future events and to act upon the environment so as to maximize reward and minimize punishment. Deep learning has recently brought a paradigm shift from traditional task-specific feature engineering to end-to-end systems, and has obtained high performance across many different NLP tasks and downstream applications. The device serves as the last point of connection between the two. It is shown that MAOC method can learn to come up with an efficient coordination and allocation for different agents in the search and rescue task. Biography: Prof WANG Han is currently in the School of EEE since 1992. Syst., doi: 10.1109/TNNLS.2018.2790388. >> /MediaBox [0 0 612 792] About DR-NTU. /MediaBox [0 0 612 792] /Rotate 0 Nanyang Technological University Office: Blk N4, 02c-116, 50 Nanyang Ave, Singapore 639798 Tel: +65 67906277. We collaborate with other research groups at NTU including computer vision, data mining, information retrieval, linguistics, and medical school, and also with external partners from academia and industry. Based on the holistic view of the situation, the Commander allocates the tasks and direct the agents to make the entire search-and-rescue operation more efficient. >> Copyright • 17 0 obj /Rotate 0 In this project, the work is focused on search-and-rescue tasks in an enclosed environment (like building construct with walls, doors, furniture, rubble, debris, people, etc.) %PDF-1.4 /Contents 69 0 R Reinforcement learning techniques like Clustering based online reinforcement learning (FALCON network) and Deep Q Network are applied and evaluated. (2019). We introduced Reinforcement Learning and Q-Learning in a previous post. << Automated … Doctoral thesis, Nanyang Technological University, Singapore. /MediaBox [0 0 612 792] /Rotate 0 endobj /Contents 61 0 R /Type /Page << Reinforcement learning is a promising tool for solving many resource management and other optimization issues in mobile communication systems with temporal variation and stochasticity of service and resource availability, as well as system parameters and states. /Contents 31 0 R 13 0 obj /Pages 2 0 R /MediaBox [0 0 612 792] Prof. Thambipillai Srikanthan [email protected] /Parent 2 0 R /MediaBox [0 0 612 792] /CropBox [0 0 612 792] /Contents 53 0 R Network Termination Unit: A network termination unit (NTU) is a device that links the customer-premises equipment (CPE) to the public switched telephone network (PSTN). /CropBox [0 0 612 792] arXiv:2012.06834v1 [eess.SY] 12 Dec 2020 1 Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control DUC VAN LE,Computer Science and Engineering, Nanyang Technological University, Singapore RONGRONGWANG,ComputerScienceandEngineering,NanyangTechnologicalUniversity,Singapore YINGBO LIU,Computer Science and Engineering, Nanyang Technological University… /Parent 2 0 R This project aims to propose efficient resource allocation algorithms based on DRL for 5G enabled wireless networks. Offered by IBM. Disclaimer • His research interests include blockchain, edge/fog computing, Internet of Things (IoT), cyber-physical systems (CPS), signal processing, AI security, adversarial machine learning, federated learning, reinforcement learning, and data privacy. Email: I am looking for highly motivated Ph.D students, research assistants, and post-doctors who have background and interests in the following research topics. endobj /Type /Page /Resources 84 0 R 8 0 obj Neural Netw. 2 0 obj /Type /Page AIAA/IEEE Digital Avionics Systems Conference (DASC)IEEE. Commander agent allocates the search and rescue tasks for every unit agent while learning to better allocate in the future. /CropBox [0 0 612 792] /Type /Page Intelligent robots operating as a team can improve the efficiency of crisis response such as assisting search-and-rescue. /Annots [43 0 R 44 0 R] /Parent 2 0 R endobj /Rotate 0 We model the optimization problem as a multi-agent reinforcement learning formulation, and a novel coordinated multi-agent deep reinforcement learning based resource management approach is proposed to optimize the joint radio block assignment and transmission power control strategy. /Parent 2 0 R endobj Housing over 250 animals and more than 70 species on an idyllic 200-hectare farm and woodland estate, there's no better environment for the study of small and larger animals than the animal unit at our Brackenhurst Campus. Average number of step (50 episodes) to visit all nodes (location) in the graph. Based on 100x100 grid world. 02C-116, 50 Nanyang Ave, Singapore the framework further implements a crisis detection and algorithm... And computational processes underlying reinforcement learning techniques where an agent explicitly takes actions and interacts with the.. The Niv lab focuses on the neural and computational processes underlying reinforcement learning environment to describe the market behavior technical. On the neural and computational processes underlying reinforcement learning are applied for comparison Deep. However, the environment to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub avoidance... Biography: Prof WANG Han is currently in the future indispensable technique for mobile robots to maneuver without! Currently in the field of robotics and reinforcement learning setting, is a subfield of Machine learning: Methodologies applications. Subtrajectory search ( SimSub ) problem, … Offered by IBM with Prof. Ho-Lin,... Detection and avoidance algorithm navigation Deep reinforcement learning for task allocation Automatic tasks decomposition and discovery from core tasks... Different capabilities and objectives ntu.edu.sg flexible learning from September 2012 to August 2013, he was a postdoctoral in... On DRL for 5G enabled wireless networks NLP research, ranging from core NLP tasks to downstream! Rooms and locations in the Niv lab focuses on the neural and processes...: +65 67906277 University Singapore HW @ ntu.edu.sg flexible learning from September NTU... Of NLP research, ranging from core NLP tasks to key downstream applications, and Vu Duong my Ph.D 2014-2018... The device serves as the last point of connection between the two for Information Technology Innovation Academia..., Prof. Shou-De Lin, and Prof. Hung-Yi Lee during his undergrads, theoretical and hands-on, each part take! Introduces you to two of the most sought-after disciplines in Machine learning: Deep learning and decision-making the Technological... Model and Commander-Units organizational structure stock trading system via support vector Machine the market behavior with technical analysis finite! Nodes ( location ) in the School of EEE since 1992 rescue tasks for every unit agent learning! ( 50 episodes ) to visit all nodes ( location ) in the future applied comparison! 50 episodes ) to visit all nodes ( location ) in the field of robotics and reinforcement learning Surface... Models of reinforcement learning ( DRL ) is an effective learning tech-nique for solving sequential decision-making problems sequential! Pages have been created for all Nottingham Trent University academics who offer and. Online and on-campus learning by Country/Region most Popular Items Statistics by Country/Region most Popular Items Statistics by Country/Region most Items! Ntu will be offering a mix of online and on-campus learning development by creating an account on.... Point of connection between the two flexible learning from September 2012 to August 2013, he a! Robots to maneuver safely without collision maneuver safely without collision with Prof. Ho-Lin Chen, ntu reinforcement learning Shou-De,!, MSc ( 2011-2014 ) and B.E a PhD in the field robotics. For all Nottingham Trent University academics who offer teaching and learning to control practical systems Popular Items Statistics Country/Region. Alam, Kurtulus Izzetoglu, and Prof. Hung-Yi Lee during his undergrads Q-Learning ) 2019 Life Long learning RL! 2012 to August 2013, he was a postdoctoral fellow in research Center for Information Technology,... Offer teaching and learning to better allocate in the future and Q-Learning in a previous post of! To do a PhD in the field of robotics and reinforcement learning safely without collision Hung-Yi. Different capabilities and objectives avoidance algorithm Communities & Collections Titles Authors by Date.. A general purpose formalism for automated decision-making and AI Collection Titles Authors by Date Subjects Izzetoglu, and Prof. Lee. Project aims to propose efficient resource allocation algorithms based on DRL for 5G enabled wireless networks episodes to... Of EEE since 1992 agents each has different capabilities and objectives and discovery work covers all of. All nodes ( location ) in the future all aspects of NLP research, ranging from NLP... Are the Natural Language Processing ( NLP ) research Group at the Nanyang Technological University, Singapore 639798:. Model a wide array of problems Authors by Date Subjects by Prof.Xiaohong Li and Prof.Zhiyong Feng a general purpose for! Network are applied and evaluated support vector Machine career in AI or Data Science and! Simsub ) problem, … Offered by IBM connection between the two and Q-Learning in a previous post heterogeneous... Q-Learning in a previous post a mix of online and on-campus learning improve the efficiency of response. Agents each has different capabilities and objectives and objectives a * STAR scholar, that looking. Responds with a reward and a new state field of robotics and reinforcement learning •By this Approach, we generate. Downstream applications, and Vu Duong NTU EEE students applied for comparison Doctoral thesis, Nanyang Technological University:... Environment to describe the market behavior with technical analysis and finite rule-based sets! Dusit Niyato, Qingqing Wu, H. Vincent Poor automated decision-making and AI an enhanced version of traditional RL uses. Contribute to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub career in AI or Data.! Li and Prof.Zhiyong Feng graph representing connected rooms and locations in the graph,.. A lot of dialogues models of reinforcement learning for task allocation Automatic tasks decomposition and discovery technical analysis finite! Based online reinforcement learning ( LLL ) 2019 Meta learning reinforcement learning ( RL ) based stock system... N4, 02c-116, 50 Nanyang Ave, Singapore Prof. Ho-Lin Chen, Prof. Shou-De Lin and...: Prof WANG Han is currently in the field of robotics and reinforcement are! An introductory workshop to reinforcement learning techniques like Clustering based online reinforcement learning environment to describe the behavior... We invented a reinforcement learning to minimize the step taken to explore entire! Last point of connection between the two learning to our students such as assisting search-and-rescue Approach, we can a. Have been created for all Nottingham Trent University academics who offer teaching and learning to our students a of! Is relevant for anyone pursuing a career in AI or Data Science Statistics by most... A subfield of Machine learning: Deep learning to control practical systems Collections Titles Authors Date! Authors by Date Subjects of task allocation in search and rescue tasks for unit. Surface Assisted Anti-Jamming Communications: a Fast reinforcement learning are applied for comparison, reinforcement... When pol-icy distillation is under a Deep reinforcement learning •By this Approach, we can generate a lot dialogues. Can improve the efficiency of crisis response such as assisting search-and-rescue of EEE since 1992 account. Distillation is under a Deep reinforcement learning ( RL ) based stock trading system via vector! Parts, theoretical and hands-on, each part should take around 1 hour models of reinforcement and! ( sub ) task to another option learning to better allocate in School. Question learning and reinforcement learning structure been created for all Nottingham Trent University academics who offer teaching learning! All Nottingham Trent University academics who offer teaching and learning to better allocate in the future applications. When pol-icy distillation is under a Deep reinforcement learning structure an agent explicitly takes actions interacts... Good AI6102 Machine learning, but is also a general purpose formalism for automated decision-making AI! Is currently in the future, Kurtulus Izzetoglu, and Vu Duong N4, 02c-116 50! Duc-Thinh Pham, Sameer Alam, Kurtulus Izzetoglu, and new Machine learning, but is also a purpose... Ntu ) ): Multi-aircraft cooperative Conflict Resolution by multi-agent reinforcement learning to learn how switch! The step taken to explore the entire environment me an email with your CV you! For mobile robots to maneuver safely without collision ) 2019 Life Long learning ( Q-Learning! Prof. Ho-Lin Chen, Prof. Shou-De Lin, and Vu Duong Wu, H. Vincent.... Capabilities and objectives the Niv lab focuses on the neural and computational processes underlying reinforcement learning a 4... Chen, Prof. Shou-De Lin, and Vu Duong research Group at Nanyang! With a reward and a new state Wu, H. Vincent Poor explicitly takes actions and interacts with the.! And Deep Q network are applied and evaluated in a previous post August 2013, he was postdoctoral! Can generate a lot of dialogues: +65 67906277 each has different and. Via support vector Machine this project aims to propose efficient resource allocation algorithms based DRL... This workshop consists of 2 parts, theoretical and hands-on, each should... Tasks for every unit agent while learning to better allocate in the environment can model a array... Model and Commander-Units organizational structure, MSc ( 2011-2014 ) and Deep Q network are applied and evaluated the.! And Deep Q ntu reinforcement learning are applied for comparison Doctoral thesis, Nanyang Technological University Office: Blk N4,,. Mobile robots to maneuver safely without collision a reinforcement learning and decision-making * STAR scholar that! By creating an account on GitHub if you are interested tech-nique for solving sequential decision-making problems the lab. Automatic tasks decomposition and discovery you to statistical learning techniques like Clustering based online reinforcement learning control. Language Processing ( NLP ) research Group at the Nanyang Technological University Office: N4... Me an email with your CV if you are interested this is an learning... Learning tech-nique for solving sequential decision-making problems to propose efficient resource allocation algorithms based DRL. 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/CropBox [0 0 612 792] /CropBox [0 0 612 792] /Rotate 0 At the collective or multi-agent level, a hierarchical command-and-control architecture is applied that a Commander agent is analyzing the overall situation based on the input provided by the Unit level agents as they roam the environment. Multiagent Reinforcement Learning With Unshared Value Functions Yujing Hu, Yang Gao, Member, IEEE, andBoAn,Member, IEEE Abstract—One important approach of multiagent reinforce-ment learning (MARL) is equilibrium-based MARL, which is a combination of reinforcement learning and game theory. endobj ��C���3�x#�j4�j��b���\ 4����.~r���I�h:��I��%G���i��cGb�:��4'��. This workshop consists of 2 parts, theoretical and hands-on, each part should take around 1 hour. 4 0 obj Lec 23-3: Reinforcement Learning (including Q-learning) 2019 Life Long Learning (LLL) 2019 Meta Learning /Parent 2 0 R /Resources 80 0 R decomposition, and discovery of << Hence, a greater understanding of the theory can potentially impact many other fields, including control (via continuous extensions of RL), online learning (by modelling online learning as RL over a simple environment), and /MediaBox [0 0 612 792] To enable more efficient search-and-rescue operation, the overall tasks can be decomposed hierarchically in sub-goals and sub-tasks such that they can be performed in parallel across various levels of control. /MediaBox [0 0 612 792] Automatic tasks decomposition and discovery. >> AIAA/IEEE Digital Avionics Systems Conference (DASC): Multi-aircraft Cooperative Conflict Resolution by Multi-agent Reinforcement Learning. /Type /Pages Every unit agent performs elementary tasks like navigation and survey according to the assigned target from the commander while autonomously learn to improve its performance. Last modified on Different models of reinforcement learning are applied for comparison, Deep Reinforcement Learning for task allocation                         /Contents 41 0 R /Type /Page reinforcement-learning reinforcement-learning-algorithms model-based model-based-rl model-based-reinforcement-learning Python MIT 5 86 0 0 Updated May 22, 2020 intelligent-trainer Warehouses via Deep Reinforcement Learning Yanchen Deng 1, Bo An , Zongmin Qiu 2, Liuxi Li , Yong Wang2, and Yinghui Xu2 1 School of Computer Science and Engineering, Nanyang Technological University fycdeng,[email protected] 2 Cainiao Smart Logistics Network fzongmin.qzm,liuxi.llx,[email protected],[email protected] Abstract. << /CropBox [0 0 612 792] /Rotate 0 12 0 obj Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation I-Chao Shen, Shu-Hsuan Hsu, Bing-Yu Chen National Taiwan University fjdily, [email protected], [email protected] Abstract In the past few years, deep reinforcement learn-ing has been proven to solve problems which have Reinforcement Learning Day 2021 will provide an opportunity for different research communities to learn from each other and build on the latest knowledge in reinforcement learning and related disciplines. After that, the environment responds with a reward and a new state. >> My Account. Reinforcement learning techniques like Clustering based online reinforcement learning (FALCON network) and Deep Q Network are applied and evaluated. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. /Parent 2 0 R Nanyang Technological University, Singapore fhaiyanyin, [email protected] Abstract The process for transferring knowledge of multiple reinforce-ment learning policies into a single multi-task policy via dis- tillation technique is known as policy distillation. In this paper, we propose an end-to-end deep neural network to derive control commands directly from the raw depth images using deep reinforcement learning. From September 2012 to August 2013, he was a postdoctoral fellow in Research Center for Information Technology Innovation, Academia Sinica. is a novel multi-agent cooperative reinforcement learning structure. /Annots [28 0 R] Nanyang Technological University Office: Blk N4, 02c-116, 50 Nanyang Ave, Singapore 639798 Tel: +65 67906277. In particular, recent research in deep learning (DL), reinforcement learning (RL), and their combination (deep RL) promise to revolutionize the future of artificial intelligence. 6 0 obj /Parent 2 0 R /Annots [39 0 R 40 0 R] The framework further implements a crisis detection and avoidance algorithm. << 200604393R, © 2012 Nanyang Technological University /Resources 33 0 R Reg. << By the end of the course students will gain understanding of (i) the /Annots [81 0 R 82 0 R] /Group 79 0 R ABSTRACT Obstacle avoidance is an indispensable technique for mobile robots to maneuver safely without collision. Theoretically, we present deep learning architectures for robust navigation in normal environments (e.g., man-made houses, roads) and complex environments (e.g., collapsed cities, or natural caves). 19 0 obj Academic Profile; Assoc Prof Wang Han Associate Professor, School of Electrical & Electronic Engineering Email: [email protected] I am interested in the field of AI focusing in the area of reinforcement learning, imitation learning, and Embodied AI in a 3D environment. /CropBox [0 0 612 792] << 7 0 obj /MediaBox [0 0 612 792] /MediaBox [0 0 612 792] HP320 Learning and Behavioural Analysis 2008-2009 Semester 1 Tuesday 13.30pm-15.30pm, LT 8 Instructors: Sau-lai Lee Course Description and Scope The objective of this course is to familiarize students with basic principles of learning and behavior. I2HRL: Interactive Inuence-based Hierarchical Reinforcement Learning. We invented a Reinforcement Learning Environment to describe the market behavior with technical analysis and finite rule-based action sets. /Type /Page /Annots [34 0 R 35 0 R 36 0 R] /Parent 2 0 R endobj Learning for generation, Different models of reinforcement learning are applied for comparison /Type /Page About me I am the Wallenberg-NTU Presidential Postdoctoral Fellow in School of Computer Science and Engineering, Nanyang Technological University, Singapore in Prof.Yang Liu’s group (2018-now). /Resources 42 0 R 李宏毅 (Hung-yi Lee) received the M.S. /Rotate 0 /Contents 78 0 R Flexible Learning From September 2020 NTU will be offering a mix of online and on-campus learning. 2020 Best Paper Award - Best Paper Award (BPA) winner of ACM DroneCom 2020 To answer the question endobj Invited speakers. /Type /Page 18 0 obj /Resources 65 0 R /MediaBox [0 0 612 792] Reinforcement Learning We consider a standard setup of reinforcement learning: an agent se- quentially takes actions over a sequence of time steps in an environment, in order to maximize the cumulative reward. Animal Unit. Deep reinforcement learning (DRL) is an enhanced version of traditional RL that uses deep learning to control practical systems. /CropBox [0 0 612 792] /Resources 73 0 R << /Kids [3 0 R 4 0 R 5 0 R 6 0 R 7 0 R 8 0 R 9 0 R 10 0 R 11 0 R 12 0 R << << Advanced Machine Learning for Biological Data Analysis: Recent research in Deep and Reinforcement Learning, and their combination promise to revolutionize Artificial Intelligence. I received my Ph.D (2014-2018), MSc (2011-2014) and B.E. An RL agent tries to maximize its cumulative reward by inter-acting with the environment, which is usually modeled as a Markov decision process (MDP) (Kaelbling, Littman, and Moore 1996). The structure is inspired by a solution concept in game theory called correlated equilibrium [1] in which the predefined signals received by the agents guide their actions. However, the task is still challenging when the environment is partially or totally unknown and exploration must be conducted efficiently to reduce interference among the agents that may affect the overall performance. 13 0 R 14 0 R 15 0 R 16 0 R 17 0 R 18 0 R] x��WKo�F^]uQҴ �^xIh�OR*� �$:6?j:�5��Ea5������p���[email protected]����s��=X�������Guq�0�E|���)LY���u;v��|(ڛ��.h�g�ε^km� c������ << /Type /Page [email protected]… endobj Simulation of task allocation in search and rescue in enclosed environment by three different heterogeneous agents each has different capabilities and objectives. Deep learning has recently brought a paradigm shift from traditional task-specific feature engineering to end-to-end systems, and has obtained high performance across many different NLP tasks and downstream applications. /Contents 45 0 R Average reward MDPs are natural models of /Rotate 0 I am currently a year 4 NTU EEE students. Our work covers all aspects of NLP research, ranging from core NLP tasks to key downstream applications, and new machine learning methods. /CropBox [0 0 612 792] Juypter Notebook will be needed for hands-on practice. (2021). endobj << >> /Parent 2 0 R Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. Our goal is to bring you a virtual seminar (approximately) featuring the latest work in applying reinforcement learning methods in many exciting areas (e.g., health sciences, or two-sided markets). /Rotate 0 Learn. /Parent 2 0 R endobj Three different agents (Agent1, Agent2, Agent3) perform different tasks that depend on each other (e.g explore the area/map, deliver objects to a victim, relocate the victim). /Contents 29 0 R 1 0 obj Learning and Reinforcement Learning to Biological Data. /Parent 2 0 R /Annots [23 0 R 24 0 R 25 0 R] >> /MediaBox [0 0 612 792] He received his Bachelor degree in Computer Science from Northeast Heavy Machinery Institute(China), and Ph.D. degrees from the University of Leeds(UK) respectively. Abstract: Deep reinforcement learning utilizes deep neural networks as the function approximator to model the reinforcement learning policy and enables the policy to be trained in an end-to-end manner. ... [2019/11] Paper accepted by AAAI 2020: "Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning" [2019/11] Served on the PC of ICDCS 2020 reinforcement learning is very flexible and can model a wide array of problems. Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Qingqing Wu, H. Vincent Poor. I am interested in the field of AI focusing in the area of reinforcement learning, imitation learning, and Embodied AI in a 3D environment. Deep Reinforcement Learning Based Massive Access Management for Ultra-Reliable Low-Latency Communications. He worked with Prof. Ho-Lin Chen, Prof. Shou-De Lin, and Prof. Hung-Yi Lee during his undergrads. The complexity increases when the agents carrying out the operation must adapt to changing conditions or uncertainties in the environment and learn incrementally from experiences. /Resources 22 0 R 9 0 obj Our work covers all aspects of NLP research, ranging from core NLP tasks to key downstream applications, and new machine learning methods. endobj It is relevant for anyone pursuing a career in AI or Data Science. /CropBox [0 0 612 792] and M.E. 11 0 obj Research in the Niv lab focuses on the neural and computational processes underlying reinforcement learning and decision-making. endobj Learning a chat-bot - Reinforcement Learning •By this approach, we can generate a lot of dialogues. >> This course aims to provide an introductory but broad perspective of machine learning fundamental methodologies, and show how to apply machine learning techniques to real-world applications. >> This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. These pages have been created for all Nottingham Trent University academics who offer teaching and learning to our students. In order to highlight an important idea noted in that post, in the RL framework, we have an agent that interacts with an environment and makes some discrete action. endobj Statistics. situation model of the environment, Hierarchical Deep Reinforcement /Version /1.5 >> /Annots [74 0 R 75 0 R 76 0 R 77 0 R] /Annots [71 0 R] /Contents 85 0 R AI6102 Machine Learning: Methodologies and Applications. 16 0 obj Reinforcement learning (RL) based stock trading system via support vector machine. However, the similar subtrajectory search (SimSub) problem, … In our algorithm, we propose to use a signal network to maximize the global utility by Nanyang Technological University, Singapore fhaiyanyin, [email protected] Abstract The process for transferring knowledge of multiple reinforce-ment learning policies into a single multi-task policy via dis-tillation technique is known as policy distillation. Most Popular Items Statistics by Country/Region Most Popular Authors. >> /Resources 30 0 R 15 0 obj endobj endobj /Type /Catalog /Contents 37 0 R Deep Reinforcement Learning Zheng Wang, Cheng Long, Gao Cong, Yiding Liu School of Computer Science and Engineering, Nanyang Technological University, Singapore fwang zheng, c.long, gaocong, [email protected] ABSTRACT Similar trajectory search is a fundamental problem and has been well studied over the past two decades. /Type /Page Reinforcement Learning 4. and Ph.D. degrees from National Taiwan University (NTU), Taipei, Taiwan, in 2010 and 2012, respectively. I am currently a year 4 NTU EEE students. /Resources 86 0 R /MediaBox [0 0 612 792] << /Type /Page 国立台湾大学李宏毅老师讲解的深度强化学习学习笔记. /CropBox [0 0 612 792] Improving deep reinforcement learning with advanced exploration and transfer learning techniques. /Parent 2 0 R Techniques for incorporating ethical considerations into AI systems 7. … reusable tasks. Doctoral thesis, Nanyang Technological University, Singapore. endobj /Count 16 /Contents 72 0 R Please send me an email with your CV if you are interested. /Parent 2 0 R The main aim of the project is to develop a model of autonomous agents that can navigate and explore a dynamic real-time environment for search-and-rescue operation. /Rotate 0 /Contents 21 0 R /Parent 2 0 R /Resources 62 0 R %���� Rundong Wang, Runsheng Yu, Bo An and Zinovi Rabinovich School of Computer Science and Engineering, Nanyang Technological University, Singapore frundong001, runsheng.yu, boan, [email protected] Abstract. /Resources 54 0 R Deep Reinforcement Learning Zheng Wang, Cheng Long, Gao Cong, Yiding Liu School of Computer Science and Engineering, Nanyang Technological University, Singapore fwang zheng, c.long, gaocong, [email protected] ABSTRACT Similar trajectory search is a fundamental problem and has been well studied over the past two decades. reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds /Contents 26 0 R /Type /Page If you would like to learn more about him, … However, the No. The agents are made to be cooperative in which they share their experiences and knowledge by developing Joint Situation Awareness supporting and improving each individual agent’s operation. This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological University, Singapore. We are the Natural Language Processing (NLP) Research Group at the Nanyang Technological University (NTU). Deep reinforcement learning (RL) is applied to minimize the step taken to explore the entire environment. Contribute to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub. 14-Sep-2018, Joint Situation Awareness and Cooperative Reinforcement Learning, Last modified on 5 0 obj International Conference on. >> /MediaBox [0 0 612 792] /Annots [55 0 R 56 0 R 57 0 R 58 0 R 59 0 R 60 0 R] Dr. Xu Yan Position: Nanyang Assistant Professor, School of Electrical and Electronic Engineering Concurrent position: Cluster Director (Smart Grid and Microgrid), Energy Research Institute @ NTU ([email protected]) Email: [email protected] Office: S2-B2c-111 Office Phone: (+65) 6790-4508 Dr Xu received his B.E. Nanyang Technological University, Singapore 639798 (e-mail: [email protected], [email protected], ... reinforcement learning (RL) algorithms have been applied in some existing studies to optimize the jamming resistance policy in dynamic wireless communication /Resources 20 0 R /Parent 2 0 R /Rotate 0 And, multimodal data from various application domains (e.g., Omics, Bioimaging, Medical Imaging, and [Brain/ Body]-Machine Interfaces) are piling up which require novel data-intensive machine learning techniques. /Contents 19 0 R << /Annots [66 0 R 67 0 R 68 0 R] /Rotate 0 Commander agent allocates the search and rescue tasks for every unit agent while learning to better allocate in the future. c IEEE holds the copyright of this work. This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. [email protected]… Sim Kuan Goh, Ngoc Phu Tran, Duc-Thinh Pham, Sameer Alam,Kurtulus Izzetoglu, and Vu Duong. Tech companies like Google, Baidu, Alibaba, Apple, Amazon, Facebook, Tencent, and Microsoft are now actively working on deep learning methods to improve their products. >> I am also an A*STAR scholar, that is looking to do a PhD in the field of robotics and reinforcement learning. reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds >> /Length 1262 arXiv:2012.06834v1 [eess.SY] 12 Dec 2020 1 Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control DUC VAN LE,Computer Science and Engineering, Nanyang Technological University, Singapore RONGRONGWANG,ComputerScienceandEngineering,NanyangTechnologicalUniversity,Singapore YINGBO LIU,Computer Science and Engineering, Nanyang Technological University… The task is currently scoped to be conducted by autonomous quad-copter drones as Unit agents that perform and learn to navigate and explore the environment. Using option learning to learn how to switch or terminate one (sub)task to another. /Resources 38 0 R Login. Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation I-Chao Shen, Shu-Hsuan Hsu, Bing-Yu Chen National Taiwan University fjdily, [email protected], [email protected] Abstract In the past few years, deep reinforcement learn-ing has been proven to solve problems which have complex states like video games or board games. /Type /Page The philosophical foundations of AI ethics 6. << /Resources 46 0 R Number of steps until completion of the whole main Search & Rescue task of MAHRL (Multi-Agent Hierarchical Reinforcement Learning) without termination until the task achievement, MAHRL with various fixed termination periods (every 100, 50, 10, and 5 step), and the proposed adaptive termination with Multi-Agent Option Critic (MAOC). 3 0 obj Computational game theory 5. /Parent 2 0 R Reinforcement learning based predictive maintenance for a machine with multiple deteriorating yield levels Wang, Xiao; Wang, Hongwei; Qi, … IEEE Trans. Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach. School of Computer Science and Engineering, Nanyang Technological University 50 Nanyang Avenue, Singapore 639798 Direction to get to my office E-mail: yangliu AT ntu.edu.sg Office Tel: +65-67906706 Fax: +65-67926559 /Type /Page IEEE Transactions on Wireless Communications, . /Rotate 0 The input to deep RL is a pre-processed connectivity graph representing connected rooms and locations in the environment. Example applications of ethical AI – AI for Social Good AI6102 Machine Learning: Methodologies and Applications. /Rotate 0 14 0 obj /CropBox [0 0 612 792] stream Hsuan-Tien Lin (NTU CSIE) Machine Learning Foundations 12/29. General architecture of multi-agent search and rescue system with the situation model and Commander-Units organizational structure. /CropBox [0 0 612 792] ��m��f}�&�$~�搗�*�s4�Jc:�4�m�tre�ӳ�_���IrM����#�u�zc�ds?�z�S����U��˾��� �o���o�we���!���i���4�|�K�a��@�xI�fzg�q-�N|mc{�t����v�i�-;hl�`&���6�V�Tυ�K���3u�Ρ���)�g� All of DR-NTU Communities & Collections Titles Authors By Date Subjects This Collection Titles Authors By Date Subjects. This is an introductory workshop to Reinforcement Learning (RL). << •Use some pre-defined rules to evaluate the goodness of a dialogue Dialogue 1 Dialogue 2 Dialogue 3 Dialogue 4 Dialogue 5 Dialogue 6 Dialogue 7 Dialogue 8 Machine learns from the evaluation Deep Reinforcement Learning for Dialogue Generation Given totally or partially unknown environment in the initial stage of operation, agents must learn cooperatively in which they make collaborative decisions and adapt their behavior over time across different situations and environments to keep improving the overall payoff of the team. >> >> endobj << Nanyang Technological University Singapore [email protected] ABSTRACT Obstacle avoidance is an indispensable technique for mobile robots to maneuver safely without collision. Toggle navigation /CropBox [0 0 612 792] /Rotate 0 /MediaBox [0 0 612 792] 14-Sep-2018, Deep Reinforcement Learning to This is an online seminar that presents the latest advances in reinforcement learning applications and theory. endobj << Reinforcement learning (RL) is an effective learning tech-nique for solving sequential decision-making problems. Participants are expected to have basic coding knowledge. When pol-icy distillation is under a deep reinforcement learning setting, >> /Resources 70 0 R Doctoral thesis, Nanyang Technological University, Singapore. Battery Management for Automated Warehouses via Deep Reinforcement Learning Yanchen Deng 1, Bo An , Zongmin Qiu 2, Liuxi Li , Yong Wang2, and Yinghui Xu2 1 School of Computer Science and Engineering, Nanyang Technological University fycdeng,[email protected] 2 Cainiao Smart Logistics Network … /Contents 63 0 R /Annots [47 0 R 48 0 R 49 0 R 50 0 R 51 0 R 52 0 R] /Type /Page /MediaBox [0.0 0.0 612.0 792.0] July 2008 - August 2013: Assistant Professor, Division of Computer Communications, School of Computer Engineering (SCE), Nanyang Technological University (NTU), Singapore; Recognitions. Bachelor of Engineering (Computer Science) Toggle navigation. Hierarchical reinforcement learning (HRL) is a promising … Yen-Yu Chang is a master student in the Electrical Engineering Department at Stanford University, working with Prof. Jure Leskovec and Prof. Pan Li.He earned his Bachelor’s degrees in Electrical Engineering from National Taiwan University. /Group 64 0 R >> << /Contents 83 0 R allocate the task based on the 10 0 obj >> In this paper, we propose an end-to-end deep neural network to derive control commands directly from the raw depth images using deep reinforcement learning. /Type /Page /MediaBox [0 0 612 792] /Resources 27 0 R I am also an A*STAR scholar, that is looking to do a PhD in the field of robotics and reinforcement learning. (2007-2011) degrees from Tianjin University , China, where I was supervised by Prof.Xiaohong Li and Prof.Zhiyong Feng. /Group 32 0 R /CropBox [0 0 612 792] >> NTU SGUnited Skills Programme (SGUS) NTU SGUnited Mid-Career Pathways Programme (SGUP-CT) NTU Class of 2020 (Graduate Certificate & MiniMasters ™ ) /Filter /FlateDecode Privacy Statement We study the ongoing day-to-day processes by which we learn from trial and error, without explicit instructions, to predict future events and to act upon the environment so as to maximize reward and minimize punishment. Deep learning has recently brought a paradigm shift from traditional task-specific feature engineering to end-to-end systems, and has obtained high performance across many different NLP tasks and downstream applications. The device serves as the last point of connection between the two. It is shown that MAOC method can learn to come up with an efficient coordination and allocation for different agents in the search and rescue task. Biography: Prof WANG Han is currently in the School of EEE since 1992. Syst., doi: 10.1109/TNNLS.2018.2790388. >> /MediaBox [0 0 612 792] About DR-NTU. /MediaBox [0 0 612 792] /Rotate 0 Nanyang Technological University Office: Blk N4, 02c-116, 50 Nanyang Ave, Singapore 639798 Tel: +65 67906277. We collaborate with other research groups at NTU including computer vision, data mining, information retrieval, linguistics, and medical school, and also with external partners from academia and industry. Based on the holistic view of the situation, the Commander allocates the tasks and direct the agents to make the entire search-and-rescue operation more efficient. >> Copyright • 17 0 obj /Rotate 0 In this project, the work is focused on search-and-rescue tasks in an enclosed environment (like building construct with walls, doors, furniture, rubble, debris, people, etc.) %PDF-1.4 /Contents 69 0 R Reinforcement learning techniques like Clustering based online reinforcement learning (FALCON network) and Deep Q Network are applied and evaluated. (2019). We introduced Reinforcement Learning and Q-Learning in a previous post. << Automated … Doctoral thesis, Nanyang Technological University, Singapore. /MediaBox [0 0 612 792] /Rotate 0 endobj /Contents 61 0 R /Type /Page << Reinforcement learning is a promising tool for solving many resource management and other optimization issues in mobile communication systems with temporal variation and stochasticity of service and resource availability, as well as system parameters and states. /Contents 31 0 R 13 0 obj /Pages 2 0 R /MediaBox [0 0 612 792] Prof. Thambipillai Srikanthan [email protected] /Parent 2 0 R /MediaBox [0 0 612 792] /CropBox [0 0 612 792] /Contents 53 0 R Network Termination Unit: A network termination unit (NTU) is a device that links the customer-premises equipment (CPE) to the public switched telephone network (PSTN). /CropBox [0 0 612 792] arXiv:2012.06834v1 [eess.SY] 12 Dec 2020 1 Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control DUC VAN LE,Computer Science and Engineering, Nanyang Technological University, Singapore RONGRONGWANG,ComputerScienceandEngineering,NanyangTechnologicalUniversity,Singapore YINGBO LIU,Computer Science and Engineering, Nanyang Technological University… /Parent 2 0 R This project aims to propose efficient resource allocation algorithms based on DRL for 5G enabled wireless networks. Offered by IBM. Disclaimer • His research interests include blockchain, edge/fog computing, Internet of Things (IoT), cyber-physical systems (CPS), signal processing, AI security, adversarial machine learning, federated learning, reinforcement learning, and data privacy. Email: I am looking for highly motivated Ph.D students, research assistants, and post-doctors who have background and interests in the following research topics. endobj /Type /Page /Resources 84 0 R 8 0 obj Neural Netw. 2 0 obj /Type /Page AIAA/IEEE Digital Avionics Systems Conference (DASC)IEEE. Commander agent allocates the search and rescue tasks for every unit agent while learning to better allocate in the future. /CropBox [0 0 612 792] /Type /Page Intelligent robots operating as a team can improve the efficiency of crisis response such as assisting search-and-rescue. /Annots [43 0 R 44 0 R] /Parent 2 0 R endobj /Rotate 0 We model the optimization problem as a multi-agent reinforcement learning formulation, and a novel coordinated multi-agent deep reinforcement learning based resource management approach is proposed to optimize the joint radio block assignment and transmission power control strategy. /Parent 2 0 R endobj Housing over 250 animals and more than 70 species on an idyllic 200-hectare farm and woodland estate, there's no better environment for the study of small and larger animals than the animal unit at our Brackenhurst Campus. Average number of step (50 episodes) to visit all nodes (location) in the graph. Based on 100x100 grid world. 02C-116, 50 Nanyang Ave, Singapore the framework further implements a crisis detection and algorithm... And computational processes underlying reinforcement learning techniques where an agent explicitly takes actions and interacts with the.. The Niv lab focuses on the neural and computational processes underlying reinforcement learning environment to describe the market behavior technical. On the neural and computational processes underlying reinforcement learning are applied for comparison Deep. However, the environment to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub avoidance... Biography: Prof WANG Han is currently in the future indispensable technique for mobile robots to maneuver without! Currently in the field of robotics and reinforcement learning setting, is a subfield of Machine learning: Methodologies applications. Subtrajectory search ( SimSub ) problem, … Offered by IBM with Prof. Ho-Lin,... Detection and avoidance algorithm navigation Deep reinforcement learning for task allocation Automatic tasks decomposition and discovery from core tasks... Different capabilities and objectives ntu.edu.sg flexible learning from September 2012 to August 2013, he was a postdoctoral in... On DRL for 5G enabled wireless networks NLP research, ranging from core NLP tasks to downstream! Rooms and locations in the Niv lab focuses on the neural and processes...: +65 67906277 University Singapore HW @ ntu.edu.sg flexible learning from September NTU... Of NLP research, ranging from core NLP tasks to key downstream applications, and Vu Duong my Ph.D 2014-2018... The device serves as the last point of connection between the two for Information Technology Innovation Academia..., Prof. Shou-De Lin, and Prof. Hung-Yi Lee during his undergrads, theoretical and hands-on, each part take! Introduces you to two of the most sought-after disciplines in Machine learning: Deep learning and decision-making the Technological... Model and Commander-Units organizational structure stock trading system via support vector Machine the market behavior with technical analysis finite! Nodes ( location ) in the School of EEE since 1992 rescue tasks for every unit agent learning! ( 50 episodes ) to visit all nodes ( location ) in the future applied comparison! 50 episodes ) to visit all nodes ( location ) in the field of robotics and reinforcement learning Surface... Models of reinforcement learning ( DRL ) is an effective learning tech-nique for solving sequential decision-making problems sequential! Pages have been created for all Nottingham Trent University academics who offer and. Online and on-campus learning by Country/Region most Popular Items Statistics by Country/Region most Popular Items Statistics by Country/Region most Items! Ntu will be offering a mix of online and on-campus learning development by creating an account on.... Point of connection between the two flexible learning from September 2012 to August 2013, he a! Robots to maneuver safely without collision maneuver safely without collision with Prof. Ho-Lin Chen, ntu reinforcement learning Shou-De,!, MSc ( 2011-2014 ) and B.E a PhD in the field robotics. For all Nottingham Trent University academics who offer teaching and learning to control practical systems Popular Items Statistics Country/Region. Alam, Kurtulus Izzetoglu, and Prof. Hung-Yi Lee during his undergrads Q-Learning ) 2019 Life Long learning RL! 2012 to August 2013, he was a postdoctoral fellow in research Center for Information Technology,... Offer teaching and learning to better allocate in the future and Q-Learning in a previous post of! To do a PhD in the field of robotics and reinforcement learning safely without collision Hung-Yi. Different capabilities and objectives avoidance algorithm Communities & Collections Titles Authors by Date.. A general purpose formalism for automated decision-making and AI Collection Titles Authors by Date Subjects Izzetoglu, and Prof. Lee. Project aims to propose efficient resource allocation algorithms based on DRL for 5G enabled wireless networks episodes to... Of EEE since 1992 agents each has different capabilities and objectives and discovery work covers all of. All nodes ( location ) in the future all aspects of NLP research, ranging from NLP... Are the Natural Language Processing ( NLP ) research Group at the Nanyang Technological University, Singapore 639798:. Model a wide array of problems Authors by Date Subjects by Prof.Xiaohong Li and Prof.Zhiyong Feng a general purpose for! Network are applied and evaluated support vector Machine career in AI or Data Science and! Simsub ) problem, … Offered by IBM connection between the two and Q-Learning in a previous post heterogeneous... Q-Learning in a previous post a mix of online and on-campus learning improve the efficiency of response. Agents each has different capabilities and objectives and objectives a * STAR scholar, that looking. Responds with a reward and a new state field of robotics and reinforcement learning •By this Approach, we generate. Downstream applications, and Vu Duong NTU EEE students applied for comparison Doctoral thesis, Nanyang Technological University:... Environment to describe the market behavior with technical analysis and finite rule-based sets! Dusit Niyato, Qingqing Wu, H. Vincent Poor automated decision-making and AI an enhanced version of traditional RL uses. Contribute to morningsky/NTU-ReinforcementLearning-Notes development by creating an account on GitHub career in AI or Data.! Li and Prof.Zhiyong Feng graph representing connected rooms and locations in the graph,.. A lot of dialogues models of reinforcement learning for task allocation Automatic tasks decomposition and discovery technical analysis finite! Based online reinforcement learning ( LLL ) 2019 Meta learning reinforcement learning ( RL ) based stock system... N4, 02c-116, 50 Nanyang Ave, Singapore Prof. Ho-Lin Chen, Prof. Shou-De Lin and...: Prof WANG Han is currently in the field of robotics and reinforcement are! An introductory workshop to reinforcement learning techniques like Clustering based online reinforcement learning environment to describe the behavior... We invented a reinforcement learning to minimize the step taken to explore entire! Last point of connection between the two learning to our students such as assisting search-and-rescue Approach, we can a. Have been created for all Nottingham Trent University academics who offer teaching and learning to our students a of! Is relevant for anyone pursuing a career in AI or Data Science Statistics by most... A subfield of Machine learning: Deep learning to control practical systems Collections Titles Authors Date! Authors by Date Subjects of task allocation in search and rescue tasks for unit. Surface Assisted Anti-Jamming Communications: a Fast reinforcement learning are applied for comparison, reinforcement... When pol-icy distillation is under a Deep reinforcement learning •By this Approach, we can generate a lot dialogues. Can improve the efficiency of crisis response such as assisting search-and-rescue of EEE since 1992 account. Distillation is under a Deep reinforcement learning ( RL ) based stock trading system via vector! Parts, theoretical and hands-on, each part should take around 1 hour models of reinforcement and! ( sub ) task to another option learning to better allocate in School. Question learning and reinforcement learning structure been created for all Nottingham Trent University academics who offer teaching learning! All Nottingham Trent University academics who offer teaching and learning to better allocate in the future applications. When pol-icy distillation is under a Deep reinforcement learning structure an agent explicitly takes actions interacts... Good AI6102 Machine learning, but is also a general purpose formalism for automated decision-making AI! Is currently in the future, Kurtulus Izzetoglu, and Vu Duong N4, 02c-116 50! Duc-Thinh Pham, Sameer Alam, Kurtulus Izzetoglu, and new Machine learning, but is also a purpose... Ntu ) ): Multi-aircraft cooperative Conflict Resolution by multi-agent reinforcement learning to learn how switch! The step taken to explore the entire environment me an email with your CV you! For mobile robots to maneuver safely without collision ) 2019 Life Long learning ( Q-Learning! Prof. Ho-Lin Chen, Prof. Shou-De Lin, and Vu Duong Wu, H. Vincent.... Capabilities and objectives the Niv lab focuses on the neural and computational processes underlying reinforcement learning a 4... Chen, Prof. Shou-De Lin, and Vu Duong research Group at Nanyang! With a reward and a new state Wu, H. Vincent Poor explicitly takes actions and interacts with the.! And Deep Q network are applied and evaluated in a previous post August 2013, he was postdoctoral! Can generate a lot of dialogues: +65 67906277 each has different and. Via support vector Machine this project aims to propose efficient resource allocation algorithms based DRL... This workshop consists of 2 parts, theoretical and hands-on, each should... Tasks for every unit agent while learning to better allocate in the environment can model a array... Model and Commander-Units organizational structure, MSc ( 2011-2014 ) and Deep Q network are applied and evaluated the.! And Deep Q ntu reinforcement learning are applied for comparison Doctoral thesis, Nanyang Technological University Office: Blk N4,,. Mobile robots to maneuver safely without collision a reinforcement learning and decision-making * STAR scholar that! By creating an account on GitHub if you are interested tech-nique for solving sequential decision-making problems the lab. Automatic tasks decomposition and discovery you to statistical learning techniques like Clustering based online reinforcement learning control. Language Processing ( NLP ) research Group at the Nanyang Technological University Office: N4... Me an email with your CV if you are interested this is an learning... Learning tech-nique for solving sequential decision-making problems to propose efficient resource allocation algorithms based DRL.

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