Call for Participation: AAAI 2021 Workshop on Reinforcement Learning in Games
Submission Deadline: November 9, 2020
Website: http://aaai-rlg.mlanctot.info/
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:
**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.
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).