Parallel asynchronous distributed computations of optimal control in large state space Markov Decision Processes

Bruno Scherrer 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper emphasizes the link between parallel asynchronous distributed computations (PADC) and Markov Decision Processes (MDPs), which are a powerful generic model for computing optimal control. We review some results arguing that reasonably small state space MDPs can be solved with PADC. We then propose a solution for extending these results when the state space is large. This shows that difficult optimal control problems have natural neural network-like solutions and suggests a general methodology for constructing neural networks.
Type de document :
Communication dans un congrès
11th European Symposium on Artificial Neural Networks - ESANN'03, Apr 2003, Bruges, Belgique, 6 p, 2003
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https://hal.inria.fr/inria-00099718
Contributeur : Publications Loria <>
Soumis le : mardi 26 septembre 2006 - 09:40:36
Dernière modification le : jeudi 11 janvier 2018 - 06:19:48

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  • HAL Id : inria-00099718, version 1

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Bruno Scherrer. Parallel asynchronous distributed computations of optimal control in large state space Markov Decision Processes. 11th European Symposium on Artificial Neural Networks - ESANN'03, Apr 2003, Bruges, Belgique, 6 p, 2003. 〈inria-00099718〉

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