Learning Reward Machines from Partially Observed Policies
Published in TMLR, 2025
This paper deals with learning reward machines (FSM) from partial expert policies.
Publications
You can also find my articles on my Google Scholar profile.
Journal Articles
Conference Papers
Efficient Reward Identification In Max Entropy Reinforcement Learning with Sparsity and Rank Priors
Published in CDC, 2025
This paper is about infusing computationally efficient priors for learning rewards in Max Entropy Inverse Reinforcement Learning.
Recommended citation: Shehab, M. L., Tercan, A., & Ozay, N. (2025). Efficient Reward Identification In Max Entropy Reinforcement Learning with Sparsity and Rank Priors. arXiv preprint arXiv:2508.07400.
Download Paper
Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning
Published in L4DC, 2024
This paper is about the Identifiability of Max Entropy Inverse Reinforcement Learning.
Recommended citation: Shehab, M. L., Aspeel, A., Aréchiga, N., Best, A., & Ozay, N. (2024, June). Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning. In 6th Annual Learning for Dynamics & Control Conference (pp. 1266-1277). PMLR.
Download Paper
Outlier-robust inverse reinforcement learning and reward-based detection of anomalous driving behaviors
Published in ITSC, 2022
This paper is about perfomring anomally detection using LP Inverse Reinforcement Learning.
Recommended citation: Li, D., Shehab, M. L., Liu, Z., Aréchiga, N., DeCastro, J., & Ozay, N. (2022, October). Outlier-robust inverse reinforcement learning and reward-based detection of anomalous driving behaviors. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 4175-4182). IEEE.
Download Paper