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.
Document type :
Conference papers
Complete list of metadatas

https://hal.inria.fr/inria-00099718
Contributor : Publications Loria <>
Submitted on : Tuesday, September 26, 2006 - 9:40:36 AM
Last modification on : Thursday, January 11, 2018 - 6:19:48 AM

Identifiers

  • HAL Id : inria-00099718, version 1

Collections

Citation

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. ⟨inria-00099718⟩

Share

Metrics

Record views

206