A Dynamic Programming Approach to Viability Problems

Pierre-Arnaud Coquelin 1, 2 Sophie Martin 3 Rémi Munos 1
1 SEQUEL - Sequential Learning
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe, LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
Abstract : Viability theory considers the problem of maintaining a system under a set of viability constraints. The main tool for solving viability problems lies in the construction of the {\em viability kernel}, defined as the set of initial states from which there exists a trajectory that remains in the set of constraints indefinitely. The theory is very elegant and appears naturally in many applications. Unfortunately, the current numerical approaches suffer from low computational efficiency, which limits the potential range of applications of this domain. In this paper we show that the viability kernel is the zero-level set of a related dynamic programming problem, which opens promising research directions for numerical approximation of the viability kernel using tools from approximate dynamic programming. We illustrate the approach using k-nearest neighbors on a toy problem in two dimensions and on a complex dynamical model for anaerobic digestion process in four dimensions.
Type de document :
Communication dans un congrès
IEEE ADPRL, Apr 2007, Hawai, United States. pp.178-184, 2007, Proceedings of the 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL 2007)
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Soumis le : vendredi 19 janvier 2007 - 14:23:56
Dernière modification le : jeudi 11 janvier 2018 - 06:22:13
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Pierre-Arnaud Coquelin, Sophie Martin, Rémi Munos. A Dynamic Programming Approach to Viability Problems. IEEE ADPRL, Apr 2007, Hawai, United States. pp.178-184, 2007, Proceedings of the 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL 2007). 〈inria-00125423〉

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