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Cooperation of Multiple Fish-like Microrobots Based on Reinforcement Learning

Jinyan Shao, Long Wang

Year
2007
Citations
5

Abstract

This paper is concerned with cooperative control of a kind of multiple fish-like microrobots. Most of previous work on multi-robot cooperation is focused on the terrestrial robots and seldom deals with underwater applications. In fact, the tasks in hydro-environment is more challenging than those in ground circumstances and need the cooperation of robots much more. In this paper, we investigate this problem in the framework of an adversarial game with several underwater microrobots. A fuzzy reinforcement learning approach is adopted to acquire cooperative behavior and a behavioral hierarchical architecture is proposed. We conduct extensive experiments to verify the effectiveness of the proposed algorithms

Keywords

Reinforcement learningComputer scienceRobotUnderwaterAdversarial systemArtificial intelligenceFuzzy logicArchitectureFish <Actinopterygii>Human–computer interaction

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