This paper describes a construction mechanism of group behavior on decentralized autonomous robotic systems with cooperation. The decentralized autonomous robotic systems refer to multiple robotic systems including many autonomous robots, such as the cellular robotic system (CEBOT). The CEBOT consists of a number of functional robotic units called "cells". In the research on the CEBOT, same as the decentralized robotic systems, it is one of the most important issues to cooperate among many robots for the group behavior and to coordinate the group behavior, since it is important to organize the behavior of each robot in the multiple robotic systems. In order to organize the behavior in dynamic environment, we proposed a concept of the "self-recognition" for the decision making of the behavior in a robotic group. In addition to the proposed concept, this paper shows the construction mechanism of group behavior using the character of attractor. Based on this idea, we present the behavioral evolution of the group robotic systems.

This paper addresses an optimization method of the group behavior on decentralized autonomous robotic systems. Decentralized autonomous robotic systems refer to multiple robotic systems, such as cellular robotic system (CEBOT). The CEBOT, which has been proposed by the authors, consists of a number of robotic units called cells. In the research on the CEBOT, the same as decentralized robotic systems, the optimization of the behavior of each robot is one of the most important issues, since it is difficult to predict the behavior of the each robot in multiple robotic systems. In order to optimize the behavior in a dynamic environment, the authors propose a concept of self-recognition for the decision making of the behavior in a group. According to the proposed concept, this paper shows the learning and adaptation strategy for the group behavior, and presents some simulation results.>