Evolving simple programs for playing Atari games

被引：36

作者：

Wilson, Dennis G. ^{[1
]}

Cussat-Blanc, Sylvain ^{[1
]}

Luga, Herve ^{[1
]}

Miller, Julian F. ^{[2
]}

机构：

[1] Univ Toulouse, IRIT CNRS UMR5505, Toulouse, France

[2] Univ York, York, N Yorkshire, England

来源：

GECCO'18: PROCEEDINGS OF THE 2018 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE | 2018年

关键词：

Games; Genetic programming; Image analysis; Artificial intelligence; IMAGE FILTERS; NEUTRALITY;

D O I：

10.1145/3205455.3205578

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Cartesian Genetic Programming (CGP) has previously shown capabilities in image processing tasks by evolving programs with a function set specialized for computer vision. A similar approach can be applied to Atari playing. Programs are evolved using mixed type CGP with a function set suited for matrix operations, including image processing, but allowing for controller behavior to emerge. While the programs are relatively small, many controllers are competitive with state of the art methods for the Atari benchmark set and require less training time. By evaluating the programs of the best evolved individuals, simple but effective strategies can be found.

引用

页码：229 / 236

页数：8

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