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cs.LG2026
Efficient Hypergradient Descent for Inverse Reinforcement Learning
Nikita Sevriukov, Anna Barabanova, Uliana Gagarina +4
Inverse reinforcement learning (IRL) aims to recover a reward function under which the resulting policy reproduces the behavior observed in expert demonstrations. A natural approac…
cs.LG2021
UVIP: Model-Free Approach to Evaluate Reinforcement Learning Algorithms
Denis Belomestny, Ilya Levin, Alexey Naumov +1
Policy evaluation is an important instrument for the comparison of different algorithms in Reinforcement Learning (RL). However, even a precise knowledge of the value function $V^π…