Spontaneous Coordinated Behavior of Robots through Reinforcement Learning

This paper deals with spontaneous behavior for cooperation among distributed autonomous robots. The robot determines its behavior depending on its experience and behaviors of other robots. Each robot feels frustration when its determination does not suit to its environment. Then, it changes its behavior to change its situation actively. Human gives the robots an evaluation function of relation of cooperation between robots. The robots acquires a model of behaviors through learning. This model is considered as the experience.

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