Inferring Probabilistic Reward Machines from Non-Markovian Reward Processes for Reinforcement Learning

Taylor Dohmen, Noah Topper, George Atia +3

The success of reinforcement learning in typical settings is predicated on Markovian assumptions on the reward signal by which an agent learns optimal policies. In recent years, th…