Learning hierarchical control structures for multiple tasks and changing environments
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RoboCup: A Challenge Problem for AI and Robotics
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We propose Extended Q-learning. To accommodate continuous state space directly and to improve its generalization capability. Through EQ-learning, an action-value function is represented by the summation of weighted base functions, and an autonomous robot adjusts weights of base functions at learning stage. Other parameters (center coordinates, variance and so on) are adjusted at unification stage where two similar functions are unified to a simpler function.