人間オペレータの個人差と習熟度のカオス・エントロピ解析とニューラル制御による獲得(<特集>D & D 2007)  [in Japanese] Chaos-Entropy Analysis and Acquisition of Individuality and Proficiency of Human Operator's Skill Using a Neural Controller(<Special Issue>D & D 2007)  [in Japanese]

It seems that the emergence of intelligence in an autonomous robot exists in the dexterity of human or creatures as complex systems and the research style and the development procedure along this approach should be necessary for realization of a real intelligent robot. On the other hand, since the severe judgment of situation is required during stabilizing control of an unstable system like an inverted pendulum on a cart by human operators, it can be expected that human operators exhibit a complex behavior occasionally. The previous paper acquired the skill of human operator and investigated the possibility of the formation of complex system in the learning process of human operators with difficult control objects. It also considered the mechanism of robustness of human operator against the disturbance. The identified neural network controller from time series data of each trial of each operator showed well the human-generated decision-making characteristics with the chaos and the large amount of disorder. This paper showed that the estimated degree of freedom of motion increases and the estimated amount of disorder decreases with an increase of proficiency. It also showed that the agreement between simulated and experimental values for the degree of freedom of motion and the entropy ratio is particularly good when the simulated wave form and the measured wave form resemble in appearance.