Abstract
It is desirable to be able to express behavioral sequences which include the ambiguous state recognition when trying to represent "human-like" behavior-decision abilities, for example, in the intelligent robot. We have already proposed the macro behavior-decision algorithm close to the one which humans use every day by utilizing fuzzy algorithms capable of expressing sequence flow and handling both crisp and fuzzy processing. In this paper, we try to express the flowchart of a fuzzy algorithm based on Fuzzy Petri Nets (FPN) and evaluate the fuzzy state transition in the system by the marking change of fuzzy truth tokens. By using this method, we can design the fuzzy algorithm that explosions of the fuzziness do not occur and analyze the system behavior. Finally, we report results of computer simulations using this method performed for an example of the behavior-decision fuzzy algorithm for an autonomous mobile robot.
