AWRL 2016 - First Asian Workshop on Reinforcement Learning

The First Asian Workshop on Reinforcement Learning (AWRL 2016)
The University of Waikato, Hamilton - November 16, 2016
In conjunction with the 8th Asian Conference on Machine Learning (ACML 2016)
** Motivation
The first Asian Workshop on Reinforcement Learning (AWRL 2016) focuses on both theoretical models and algorithms of reinforcement learning (RL) and its practical applications. In the last few years, we have seen the growing interest in RL of researchers from different research areas and industries. We invite reinforcement learning researchers and practitioners to participate in this world-class gathering. We intend to make this an exciting event for researchers and practitioners in RL worldwide, not only for the presentation of top quality papers, but also as a forum for the discussion of open problems, future research directions and application domains of RL. AWRL 2016 will consist of keynote talks (TBA), contributed paper presentations, discussion sessions spread over a one-day period.
Reinforcement learning (RL) is an active field of research that deals with the problem of (single or multiple agents') sequential decision-making in unknown possibly partially observable domains, whose (potentially non-stationary) dynamics may be deterministic, stochastic or adversarial. RL's objective is to develop agents' capability of learning optimal policies in unknown environments (possibly in face of other coexisting agents) by trial-and-error and with limited supervision. 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 robotics systems. We would like to create a forum to discuss interesting results both theoretically and empirically related with RL. The ultimate goal of this workshop 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 workshop will cover a range of sub-topics in RL, from theoretical aspects to empirical evaluations, including but not limited to:
- Exploration/Exploitation
- Function approximation in RL
- Deep RL
- Policy search methods
- Batch RL
- Kernel methods for RL
- Evolutionary RL
- Partially observable RL
- 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
- Knowledge Representation in RL
- Hierarchical RL
- Interactive RL
- RL in psychology and neuroscience
- Applications of RL, e.g.: Recommender systems, Robotics, Video games, Finance...
**Paper Submission
Workshop submissions and camera ready versions will be handled by EasyChair. Click here for submission.
Papers should be formatted according to the ACML formatting instructions for the Conference Track. Submissions need not be anonymous.
AWRL is a non-archival venue and there will be no published proceedings. However, the papers will be posted on this website. Therefore it will be possible to submit to other conferences and journals both in parallel to and after AWRL 2016. Besides, we also welcome submissions to AWRL that are under review at other conferences and workshops. For this reason, please feel free to submit either anonymized or non-anonymized versions of your work. We have enabled anonymous reviewing so EasyChair will not reveal the authors unless you chose to do so in your PDF.
At least one author from each accepted paper must register for the workshop. Please see the ACML 2016 Website for information about accommodation and registration.
** Important Dates
Submission deadline: Aug. 31, 2016
Notification of acceptance: Oct. 10, 2016
Camera ready deadline: Oct. 24, 2016
Workshop date: Nov. 16, 2016
ACML dates: Nov. 16-18, 2016
** Organizing Committee
Jianye Hao, Tianjin University, China
Paul Weng, SYSU-CMU Joint Institute of Engineering, China
Yang Yu, Nanjing University, China
Zongzhang Zhangi, Soochow University, China