Evolving communicating agents based on genetic programming

Author

Iba, Hitoshi ; Nozoe, Toshihide ; Ueda, Kanji

Author_Institution

Electrotech. Lab., Ibaraki, Japan

fYear

1997

fDate

13-16 Apr 1997

Firstpage

297

Lastpage

302

Abstract

The paper presents the emergence of the cooperative behavior for communicating agents by means of genetic programming (GP). Our experimental domain is the pursuit game, a multi agent test bed. The world consists of simulated robot agents and a simulated environment which is both dynamic and unpredictable. For the purpose of evolving the cooperative behavior, we use the co-evolutionary breeding strategy. We confirm the emergence of cooperation via communication. The effectiveness of GP based multi agent learning is discussed with comparative experiments

Keywords

cooperative systems; digital simulation; games of skill; genetic algorithms; intelligent control; learning (artificial intelligence); linear programming; software agents; GP based multi agent learning; co-evolutionary breeding strategy; communicating agents; comparative experiments; cooperative behavior; evolving communicating agents; genetic programming; multi agent test bed; pursuit game; simulated environment; simulated robot agents; Artificial intelligence; Cloning; Genetic programming; Intelligent agent; Laboratories; Learning; Multiagent systems; Robot kinematics; Robustness; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1997., IEEE International Conference on

Conference_Location

Indianapolis, IN

Print_ISBN

0-7803-3949-5

Type

conf

DOI

10.1109/ICEC.1997.592321

Filename

592321