الباحثون

Chris Martens

المنشورات 2

نسخة أولية وصول مفتوح

Learning Explainable Representations of Complex Game-playing Strategies

As part of learning to play complex games, human players develop develop abstractions for concepts and strategies of gameplay consistent with game rules to improve their performance. These concepts are applied to explain other players' actions, and to inform their own actions in-game. Understanding other players' strat …

نسخة أولية وصول مفتوح

Towards the Automatic Synthesis of Interpretable Chess Tactics

State-of-the-art reinforcement learning agents are capable of outperforming human experts at games like chess, Go and StarCraft II. These agents do not simply take advantage of their digital hardware in being able to react and calculate faster than humans, but employ better strategies that lead to more victories. Inter …

المؤلفون المشاركون