2019
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards
NeurIPS 2019poster
We propose a new complexity measure for Markov decision processes (MDPs), the maximum expected hitting cost (MEHC). This measure tightens the closely related notion of diameter [JOA10] by accounting for the reward structure. We show that this parameter replaces diameter in the upper bound on the opt…