JACIII Vol.16 No.1 pp. 139-146
doi: 10.20965/jaciii.2012.p0139


Adaptive Cooperation for Multi Agent Systems Based on Human Social Behavior

Hiroshi Igarashi*, Yoshinobu Adachi**,
and Kazunari Takahashi***

*Department of Electrical and Electronic Engineering, Tokyo Denki University, 2-2 Kanda-Nishiki-cho, Chiyoda-ku, Tokyo 101-8457, Japan

**Intelligent Systems Laboratory, SECOM Co., Ltd., 8-10-16 Shimorenjaku, Mitaka, Tokyo 181-8528, Japan

***Department of Information and Computer Sciences, Saitama University, 255 Shimo-Okubo, Sakura, Saitama 338-8570, Japan

May 23, 2011
August 17, 2011
January 20, 2012
multi agent systems, cooperation, social interaction
This paper addresses a new cooperation technique for multi-agent systems. This technique is based on human social behaviour. According to biological knowledge, the population contributes to the preservation of the species and adaptability to environmental variations. Multiple robot cooperation, therefore, has a potential to be flexible and adaptable to various tasks. Furthermore, sociality based on the performance evaluation of other humans is expected to enhance the whole task performance. Finally, adaptability and the total performance of proposed technique are verified by pursuit survey on the multi-agent system.
Cite this article as:
H. Igarashi, Y. Adachi, and K. Takahashi, “Adaptive Cooperation for Multi Agent Systems Based on Human Social Behavior,” J. Adv. Comput. Intell. Intell. Inform., Vol.16 No.1, pp. 139-146, 2012.
Data files:
  1. [1] T. Balch and R. C. Arkin, “Behavior-based Formation Control for Multi-Robot Teams,” IEEE Trans. on Robotics and Automation, Vol.14, No.6, pp. 926-939, 1998.
  2. [2] L. Leimin and L. Gang, “On Multi-Robot Cooperation based on MAS and Sensor Information,” Proc. of IEEE Conf. on Computational Complexity 2008, pp. 500-504, 2008.
  3. [3] J. H. Fewell, “Social Insect Networks,” Science, Vol.301, No.5641, pp. 1867-1870, 2003.
  4. [4] S. Kawamura, “Human Dexterity and Machine Dexterity How does Dexterity of Robots Emerge,” J. of robotics Society Japan, Vol.16, No.5, pp. 586-590, 1998.
  5. [5] R. Alexander, “The Challenge of Human Social Behavior,” Evolutionary Psychology, Vol.4, pp. 1-32, 2006.
  6. [6] A. Spink and C. Cole, “Information Behavior: A Socio-Cognitive Ability,” Evolutionary Psychology, Vol.5, No.2, pp. 257-274, 2007.
  7. [7] A. F. G. Bourke, “Colony Size, Social Complexity and Reproductive Conflict in Social Insects,” J. of Evolutionary Biology, Vol.12, Issue 2, pp. 245-257, 2001.
  8. [8] E. P. Dimuro et al., “Centralized Regulation of Social Exchanges Between Personality-Based Agents,” COIN 2006 Workshops, LNAI 4386, pp. 338-355, 2007.
  9. [9] T. Shiose, M. Okada, et al., “An Emergent Mechanism of Sociality by Bi-referential Model: Social Norm Acquired through Playing Primitive Soccer,” IPSJ SIG Notes. ICS, Information Processing Society of Japan, Vol.98, No.4, pp. 79-86, 1998.
  10. [10] K. Takahashi and M. Kakikura, “Research on Cooperative Capture by Multiple Mobile Robots – A Proposition of Cooperative Capture Strategies in the Pursuit Problem –,” Proc. of Distributed Autonomous Robotic Systems 2002, pp. 393-402, 2002.
  11. [11] L. Ross, D. Greene, and P. House, “The False Consensus Effect: An egocentric bias in social perception and attribution process,” J. of Experimental Social Psychology, Vol.13, pp. 279-301, 1977.
  12. [12] B. D. Bernheim, “A Theory of Conformity,” J. of Political Economy, Vol.102, No.5, pp. 841-877, 1994.
  13. [13] H. Igarashi, F. Hasegawa, and K. Takahashi, “Adaptive Cooperation for Multiple Robots Based on Human Social Behaviour: Evaluation of Adaptation in Cooperative Capturing Task with Disturbance,” Proc. of The 13th Robotics Symposia, pp. 326-331, 2008.

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