Self-organized acquisition of situated behaviors

The paper aims at a systematic approach to the self-organization of behavior. It is rooted in the ideas of situated artificial intelligence and introduces situated behavior as the target for the self-organization procedure. Based on a quantitative measure of behavioral situatedness a learning dynamics is introduced which enables the controller to sustain the situatedness of the agent. The principle is demonstrated with Khepera robots in a number of different environmental conditions.