| Contrastive explanations for comparing preferences of reinforcement learning agents J Gajcin, R Nair, T Pedapati, R Marinescu, E Daly, I Dusparic arXiv preprint arXiv:2112.09462, 2021 | 12* | 2021 |
| Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities J Gajcin, I Dusparic ACM Computing Surveys 56 (9), 1-33, 2024 | 9 | 2024 |
| Reccover: Detecting causal confusion for explainable reinforcement learning J Gajcin, I Dusparic International Workshop on Explainable, Transparent Autonomous Agents and …, 2022 | 9 | 2022 |
| Causal counterfactuals for improving the robustness of reinforcement learning T He, J Gajcin, I Dusparic arXiv preprint arXiv:2211.05551, 2022 | 5 | 2022 |
| Raccer: Towards reachable and certain counterfactual explanations for reinforcement learning J Gajcin, I Dusparic arXiv preprint arXiv:2303.04475, 2023 | 3 | 2023 |
| Iterative Reward Shaping using Human Feedback for Correcting Reward Misspecification J Gajcin, J McCarthy, R Nair, R Marinescu, E Daly, I Dusparic Proceedings of the 2023 European Conference on Artificial Intelligence, 2023 | 2 | 2023 |
| Counterfactual Explanations for Reinforcement Learning Agents J Gajcin Proceedings of the 2023 International Conference on Autonomous Agents and …, 2023 | 1 | 2023 |
| ACTER: Diverse and Actionable Counterfactual Sequences for Explaining and Diagnosing RL Policies J Gajcin, I Dusparic arXiv preprint arXiv:2402.06503, 2024 | | 2024 |
