Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces

Angeliki Kamoutsi, Peter Schmitt-Förster, Tobias Sutter +2

This work studies discrete-time discounted Markov decision processes with continuous state and action spaces and addresses the inverse problem of inferring a cost function from obs…