Patrinos, Panagiotis and Sarimveis, Haralambos An RBF based neuro-dynamic approach for the control of stochastic dynamic systems. In: 16th IFAC World Congress, 3-8 July 2005, Prague, Czech Republic (2005)Full text not available from this repository.
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.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||Q Science > QA Mathematics
T Technology > TJ Mechanical engineering and machinery
|Research Area:||Computer Science and Applications|
|Depositing User:||Ms T. Iannizzi|
|Date Deposited:||06 Dec 2011 10:51|
|Last Modified:||06 Dec 2011 10:51|
Actions (login required)