A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions

Pratik Gajane, Ronald Ortner, Peter Auer

We consider reinforcement learning in changing Markov Decision Processes where both the state-transition probabilities and the reward functions may vary over time. For this problem…