** Submission Deadline: November 9, 2020 **
Games provide an abstract and formal model of environments in which multiple agents interact: each player has a well-defined goal and rules to describe the effects of interactions among the players. The first achievements in playing these games at super-human level were attained with methods that relied on and exploited domain expertise that was designed manually (e.g. chess, checkers). In recent years, we have seen examples of general approaches that learn to play these games via self-play reinforcement learning (RL), as first demonstrated in Backgammon. While progress has been impressive, we believe we have just scratched the surface of what is capable, and much work remains to be done in order to truly understand the algorithms and learning processes within these environments.
The main objective of the workshop is to bring researchers together to discuss ideas, preliminary results, and ongoing research in the field of reinforcement in games.
We invite participants to submit papers on the 9th of November, based on but not limited to, the following topics:
- RL in various formalisms: one-shot games, turn-based, and Markov games, partially-observable games, continuous games, cooperative games
- Deep RL in games
- Combining search and RL in games
- Inverse RL in games
- Foundations, theory, and game-theoretic algorithms for RL
- Opponent modeling
- Analyses of learning dynamics in games
- Evolutionary methods for RL in games
- RL in games without the rules
- Monte Carlo tree search
- Online learning in games.
Format of workshop
RLG is a 1 full-day workshop. It will start a 60 minute mini-tutorial covering a brief tutorial and basics of RL in games, 2-3 invited talks by prominent contributors to the field, paper presentations, a poster session, and will close with a discussion panel.
Submission requirements
Papers must be between **4-8 pages ** in the AAAI submission format, with the eighth page containing only references. Papers will be submitted electronically using Easychair. Accepted papers will not be archival, and we explicitly allow papers that are concurrently submitted to, currently under review at, or recently accepted in other conferences / venues.
Please submit your paper using the submission link on the web site.
Workshop Chair: Martin Schmid (DeepMind)
Workshop committee: Marc Lanctot (DeepMind), Julien Perolat (DeepMind), Martin Schmid (DeepMind).
