Sciweavers

Share
SAB
2010
Springer

TeXDYNA: Hierarchical Reinforcement Learning in Factored MDPs

9 years 5 months ago
TeXDYNA: Hierarchical Reinforcement Learning in Factored MDPs
Reinforcement learning is one of the main adaptive mechanisms that is both well documented in animal behaviour and giving rise to computational studies in animats and robots. In this paper, we present TeXDYNA, an algorithm designed to solve large reinforcement learning problems with unknown structure rating hierarchical abstraction techniques of Hierarchical Reinforcement Learning and factorization techniques of Factored Reinforcement Learning. We validate our approach on the LIGHT BOX problem.
Olga Kozlova, Olivier Sigaud, Christophe Meyer
Added 14 Feb 2011
Updated 14 Feb 2011
Type Journal
Year 2010
Where SAB
Authors Olga Kozlova, Olivier Sigaud, Christophe Meyer
Comments (0)
books