Applying Dynamic Networks to Improve Learning Performances of An Evolutionary Behavior Programming System for Mobile Robots in Dynamic Environments

A behavior-based approach has been effectively applied for the design of robot control systems, and evolutionary algorithms have also been im-plemented as the approach to generate the robot control systems automatically. In this paper, we propose an integration of both concepts as an automatic behavior programming system. By adapting from the idea of Behavior Analysis (Colombetti, Dorigo and Borghi, 1996), Behav-ioral Modules and Interactions are presented in order to be able to represent behavior-based con-trol systems in programming paradigm. Then, the processes of Genetic Programming are ap-plied to discover the possible behavior-base