DocumentCode :
3565772
Title :
Genetic algorithms for coordinating multi-agent robotic systems
Author :
Lin, Fang-Chang
Author_Institution :
Commun. Network Lab., Inst. for Inf. Ind., Taipei, Taiwan
Volume :
4
fYear :
1997
Firstpage :
3431
Abstract :
This paper provides a genetic algorithm for solving the object-sorting task. The object-sorting task is a complex multi-agent task which requires the cooperation of multiple agents for searching and moving the objects to their destinations. The agent-object sequence is utilized to represent the solutions and for performance evaluation. The object-agent sequence is developed for chromosome representation and GA operations. A distributed help model and a centralized furniture mover model are used for performance comparison. The experimental results showed that the GA is better than the two compared models. In addition, each chromosome operated in the evolution process is designed to be feasible so as to reduce the execution time
Keywords :
genetic algorithms; mobile robots; path planning; performance evaluation; agent-object sequence; centralized furniture mover model; chromosome representation; complex multi-agent task; distributed help model; genetic algorithms; multi-agent robotic systems coordination; object-sorting task; performance evaluation; Biological cells; Biological information theory; Evolution (biology); Genetic algorithms; Mobile robots; Pediatrics; Process design; Robot kinematics; Service robots; Sorting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
ISSN :
1062-922X
Print_ISBN :
0-7803-4053-1
Type :
conf
DOI :
10.1109/ICSMC.1997.633183
Filename :
633183
Link To Document :
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