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A Learning Architecture of a Cooperative Behavior for a Group of Mobile Robots that Capture Fleeing Targets

Eiichi Horiuchi, Kazuo Tani

Year
1994
Citations
3
Access
Open access

Abstract

A learning architecture with a distributable genetic algorithm (dGA) that enables a robot system to obtain a cooperative group behavior is presented. This report focuses on the cooperation issues in a fleeing target capturing problem; mobile robots are commanded to capture fleeing targets in a 2D environment and the task requires a cooperation among mobile robots.

Keywords

RobotMobile robotCrossoverSelection (genetic algorithm)Artificial intelligenceTask (project management)Computer scienceSimilarity (geometry)Genetic algorithmHuman–computer interaction

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