Smoothing-Evaluation Method in Delayed Reinforcement Learning
نویسندگان
چکیده
Another method of delayed reinforcement learning is proposed. There are two neural networks in a robot's brain, those are a evaluation network and a motion network. The evaluation network is trained so as to reduce the absolute value of the second order time derivative of the output of itself while the robot moves. The learning realize the evaluation by the necessary time until a robot gets a target and the route of a robot can be optimized under some conditions. In a simulation, a robot with an asymmetric motion characteristic could get a target along an almost optimal route, that is better than that in a comparison simulation that the evaluation function is given by the authors and only the motion is learned.
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