A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning

In this paper we consider the problem of how a reinforcement learning agent that is tasked with solving a sequence of reinforcement learning problems (Markov decision processes) can use knowledge acquired early in its lifetime to improve its ability to solve new problems. Specifically, we focus on the question of how the agent should expl...More