%0 Conference Paper
%A Patrinos, Panagiotis
%A Sarimveis, Haralambos
%B 16th IFAC World Congress
%C Prague, Czech Republic
%D 2005
%F eprints:1035
%T An RBF based neuro-dynamic approach for the control of stochastic dynamic systems
%U http://eprints.imtlucca.it/1035/
%X This paper presents a neuro-dynamic programming methodology for the control of markov decision processes. The proposed method can be considered as a variant of the optimistic policy iteration, where radial basis function (RBF) networks are employed as a compact representation of the cost-to-go function and the ॕ-LSPE is used for policy evaluation. We also emphasize the reformulation of the Bellman equation around the post-decision state in order to circumvent the calculation of the expectation. The proposed algorithm is applied to a retailer-inventory management problem.