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《Proceedings of 2010 Chinese Control and Decision Conference》2010年
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Reinforcement Learning Method Based on Semi-parametric Regression Model

【摘要】:正In order to make full use of the advantages of both parametric and non-parametric models simultaneously,a kind of semi-parametric support vector machine(SVM) was proposed by combining a non-parametric SVM model and a parametric linear basis function model.The semi-parametric SVM was used to estimate the Q values of continuous-state-discontinuous-action pairs in an on-line manner so as to generalize a standard Q learning method to continuous state spaces.Simulation results concerning the balancing control problem of an inverted pendulum show that the proposed Q learning method has good adaptability for changes of system parameters and initial states,which provides a new approach to solve the generalization problem of continuous space of reinforcement learning.

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