Scope and Background:
Reinforcement learning (RL) is an active field of research that deals with the problem of (single or multiple agents') sequential decision-making in unknown and possibly partially observable domains, whose dynamics may be deterministic, stochastic or adversarial. In the last few years, we have seen a growing interest in RL from both research communities and industries, and recent developments in exploration-exploitation, online learning, planning, and representation learning are making RL more and more appealing to real-world applications, with promising results in challenging domains such as recommendation systems, computer games, or robotic control.
This special track focuses on both theoretical models and algorithms of RL and its practical applications in various domains. The ultimate goal is to bring together diverse viewpoints in the RL area in an attempt to consolidate the common ground, identify new research directions, and promote the rapid advance of RL research community.
Topics:
The special track will cover a range of sub-topics in RL, from theoretical aspects to empirical evaluations, including but not limited to:
Exploration/exploitation
Deep RL, function approximation in RL
Policy search methods
Batch RL
Kernel methods for RL
Evolutionary RL
Partially observable RL, POMDP, predictive state representations
Bayesian RL
Multi-agent RL
RL in non-stationary domains
Life-long RL
Non-standard Criteria in RL, e.g., risk-sensitive RL, multi-objective RL, preference-based RL
Transfer Learning in RL
Model-based RL, simulation-based RL, planning-based RL
Knowledge representation in RL
Hierarchical RL
Interactive RL
Planning under uncertainty
RL in psychology and neuroscience
Applications of RL, e.g., in recommender systems, robotics, video games, finance, autonomous driving, healthcare.
Track Chairs:
Chao Yu, Dalian University of Technology, China
Jianye Hao, Tianjin University, China
Yang Yu, Nanjing University, China
Zongzhang Zhang, Soochow University, China
Track PC members:
Daan Bloembergen, Centrum Wiskunde & Informatica, Netherlands
Siqi Chen, Southwest University, China
Yingke Chen, Sichuan University, China
Jen Jen Chung, ETH Zürich, Switzerland
Qiming Fu, Suzhou University of Science and Technology, China
Yang Gao, Nanjing University, China
Jianye Hao, Tianjin University, China
Jianmin Ji, University of Science and Technology of China, China
Yichuan Jiang, Southeast University of China, China
Guangliang Li, Ocean University of China, China
Wee Sun Lee, National University of Singapore, Singapore
Qiang Lv, Yangzhou University, China
Feng Wu, University of Science and Technology of China, China
Paul Weng, University of Michigan-Shanghai Jiaotong University, China
Yifeng Zeng, Teesside University, UK
Yingfeng Chen, Netease, China
Quan Liu, Soochow University, China
Xian Guo , Nankai University, China
Chao Yu, Dalian University of Technology, China
Yang Yu, Nanjing University, China
Zongzhang Zhang, Soochow University, China
Li Zhao, Microsoft Research Asia, China