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math.OC2024
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…
math.OC2017★ 13 cited
On Infinite Linear Programming and the Moment Approach to Deterministic Infinite Horizon Discounted Optimal Control Problems
Angeliki Kamoutsi, Tobias Sutter, Peyman Mohajerin Esfahani +1
We revisit the linear programming approach to deterministic, continuous time, infinite horizon discounted optimal control problems. In the first part, we relax the original problem…