2 papers
cs.LG2021
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
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…