학술논문
Human-level control through deep reinforcement learning
Document Type
redif-article
Author
Source
Nature, Nature. 518(7540):529-533
Subject
Language
English
Abstract
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.