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Second-order training of adaptive critics for online process control

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3 Author(s)
Govindhasamy, J.J. ; Res. Group, Queen''s Univ. Belfast, UK ; McLoone, S.F. ; Irwin, G.W.

This paper deals with reinforcement learning for process modeling and control using a model-free, action- dependent adaptive critic (ADAC). A new modified recursive Levenberg Marquardt (RLM) training algorithm, called temporal difference RLM, is developed to improve the ADAC performance. Novel application results for a simulated continuously-stirred-tank-reactor process are included to show the superiority of the new algorithm to conventional temporal-difference stochastic backpropagation.

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Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:35 ,  Issue: 2 )