Gabriel Paludo Licks

Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision Processes

Our work aims at developing reinforcement learning algorithms that do not rely on the Markov assumption. We consider the class of Non-Markov Decision Processes where histories can be abstracted into a finite set of states while preserving the dynamics. We call it a Markov abstraction since it induce…