Human-level control through deep reinforcement learning
Nature, 518 (7540):
529--533 (2015)DOI: 10.1038/nature14236
Zusammenfassung
An artificial agent is developed that learns to play a diverse range of classic Atari 2600 computer games directly from sensory experience, achieving a performance comparable to that of an expert human player; this work paves the way to building general-purpose learning algorithms that bridge the divide between perception and action.
Beschreibung
Human-level control through deep reinforcement learning | Nature
