Evaluation on flexibility of swarm intelligent system

Many studies on swarm intelligent systems have been presented. However, analytical treatment on swarm intelligence has not been performed sufficiently, because of difficulties in finding general criteria to evaluate system performance. In this paper, we regard flexibility as one property of the robustness, and evaluate the flexibility of swarm intelligent systems. We propose indexes to evaluate the behavior of swarm intelligent systems, which focus an "flexibility". The proposed indexes provide a way to compare the performance between different swarm intelligent systems. We apply the indexes to evaluate two swarm intelligent systems using computer simulation, and discuss the results.

[1]  Toshio Fukuda,et al.  Micro autonomous robotic system and biologically inspired immune swarm strategy as a multi agent robotic system , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[2]  Jing Wang,et al.  Distributed computing problems in cellular robotic systems , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[3]  Maja J. Matarić,et al.  From Local Interactions to Collective Intelligence , 1995 .

[4]  Giulio Sandini,et al.  Instinctive behaviors and personalities in societies of cellular robots , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[5]  NOBUO SANNOMIYA,et al.  A simulation study on autonomous decentralized mechanism in fish behaviour model , 1996, Int. J. Syst. Sci..

[6]  G. Beni,et al.  The concept of cellular robotic system , 1988, Proceedings IEEE International Symposium on Intelligent Control 1988.

[7]  Toshio Fukuda,et al.  Intention Model and Coordination for Collective Behavior in Group Robotic System , 1994, DARS.