A Reinforcement Learning Based ART2 Neural Network: RL-ART2
FAN Jian1,2, FEI Mei-Rui1
1.Key Laboratory of Power Station Automation Technology, Shanghai University, Shanghai 2000722. Operations Research Centre, Nanjing Army Command College, Nanjing 210045
Abstract A reinforcement learning based ART2 neural network (RLART2) is proposed and its learning algorithm is given. It is capable of online learning without training samples by using the characteristic of alteration with environment of reinforcement learning. In RLART2, the output classified pattern is got by inner competition of ART2, then the running effect of the classified pattern is gained and evaluated through altering with environment. With enough time of being online and interactive learning with environment, a certain recognition ratio of ART2 neural network is attained. The simulation results of path planning for mobile robot indicate that the collision times of robot is effectively decreased by using RLART2 . Moreover, the rationality and validity of RLART2 are also demonstrated by the results.
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2008, Vol. 21 
