Generation of behavior automaton on neural network

To plan behavior procedures, it is necessary for an agent to have a world model concerning the temporal sequences information. In this paper, a temporal information learning algorithm is proposed with a three layer neural network implementing the "effectiveness of simulation accumulation" algorithm. This algorithm can construct a "behavior automaton" in the neural network. From the results of some learning experiments using a mobile robot simulation, the generated automaton expresses the complexity of the simulation environments. The robot agent acquires a behavior automaton for obstacle avoidance behavior which is influenced by the simulation environment.