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The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a collection of random variables. Factored Reinforcement Learning (FRL) is an Model-based Reinforcement Learning approach to FMDPs w ...

Factored Reinforcement Learning (FRL) is a method to solve Factored Markov Decision Processes when the structure of the transition and reward functions of the problem must be learned. In this paper, we present TeXDYNA, an algorithm that combines the abstraction techniques of Semi-Markov Decision Pro ...