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Algebraic results and bottom-up algorithm for policies generalization in reinforcement learning using concepts lattices

Marc Ricordeau 1 Michel Liquière 2 
2 COCONUT - Agents, Apprentissage, Contraintes
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
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Conference papers
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00378912
Contributor : Isabelle Gouat Connect in order to contact the contributor
Submitted on : Monday, April 27, 2009 - 12:07:26 PM
Last modification on : Friday, August 5, 2022 - 3:02:57 PM

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  • HAL Id : lirmm-00378912, version 1

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Marc Ricordeau, Michel Liquière. Algebraic results and bottom-up algorithm for policies generalization in reinforcement learning using concepts lattices. ICHSA'06: International Conference on Hybrid Systems and Applications, Lafayette, LA, USA, pp.N/A. ⟨lirmm-00378912⟩

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