8 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 2 cited
A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio
Inverse reinforcement learning (IRL) is the task of finding a reward function that generates a desired optimal policy for a given Markov Decision Process (MDP). This paper develops…
cs.LG2019★ 8 cited
On the Correctness and Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio
Inverse reinforcement learning (IRL) is the problem of finding a reward function that generates a given optimal policy for a given Markov Decision Process. This paper looks at an a…