Reinforcement learning and games have a long and mutually beneficial common history.
From one side, games are rich and challenging domains for testing reinforcement learning …

It is widely agreed that the field of reinforcement learning would benefit from the
establishment of standard benchmark problems and perhaps regular competitive events …

Recent progress in the field of reinforcement learning has been accelerated by virtual
learning environments such as video games, where novel algorithms and ideas can be …

Video games provide a rich testbed for artificial intelligence methods. In particular, creating
automated opponents that perform well in strategy games is a difficult task. For instance …

In this textbook the author takes as inspiration recent breakthroughs in game playing to
explain how and why deep reinforcement learning works. In particular he shows why two …

. This article reports on the reinforcement learning competitions, which have been held
annually since 2006. In these events, researchers from around the world developed …

Reinforcement learning (RL) algorithms update an agent's parameters according to one of
several possible rules, discovered manually through years of research. Automating the …

OpenSpiel is a collection of environments and algorithms for research in general
reinforcement learning and search/planning in games. OpenSpiel supports n-player (single …

Performance evaluations are critical for quantifying algorithmic advances in reinforcement
learning. Recent reproducibility analyses have shown that reported performance results are …

In artificial intelligence the aim is to build intelligent entities (Russell and Norvig, 2009).
According to some, an artificial entity can be called intelligent when it can successfully mimic …