|Online Evolution for Cooperative Behavior in Group Robot Systems
Dong-Wook Lee, Sang-Wook Seo, and Kwee-Bo Sim*
International Journal of Control, Automation, and Systems, vol. 6, no. 2, pp.282-287, 2008
Abstract : In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.
Keyword : Cooperative behavior, distributed evolutionary algorithm, distributed mobile robot system, dxperience-based crossover, Q-learning, reinforcement learning.