Comparison of RBF Network Learning and Reinforcement Learning on the Maze Exploration Problem
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چکیده
An emergence of intelligent behavior within a simple robotic agent is studied in this paper. Two control mechanisms for an agent are considered — a radial basis function neural network trained by evolutionary algorithm, and a traditional reinforcement learning algorithm over a finite agent state space. A comparison of these two approaches is presented on the maze exploration problem.
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تاریخ انتشار 2008