Contrastive Explanations for Comparing Preferences of Reinforcement Learning Agents. - Jasmina Gajcin; Rahul Nair; Tejaswini Pedapati; Radu Marinescu 002; Elizabeth Daly; Ivana Dusparic (CoRR, 2021)

ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning. - Jasmina Gajcin; Ivana Dusparic (EXTRAAMAS@AAMAS, 2022)

Counterfactual Explanations for Reinforcement Learning. - Jasmina Gajcin; Ivana Dusparic (CoRR, 2022)

Causal Counterfactuals for Improving the Robustness of Reinforcement Learning. - Tom He; Jasmina Gajcin; Ivana Dusparic (CoRR, 2022)

Counterfactual Explanations for Reinforcement Learning Agents. - Jasmina Gajcin (AAMAS, 2023)

Iterative Reward Shaping Using Human Feedback for Correcting Reward Misspecification. - Jasmina Gajcin; James McCarthy; Rahul Nair; Radu Marinescu 002; Elizabeth Daly; Ivana Dusparic (ECAI, 2023)

RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning. - Jasmina Gajcin; Ivana Dusparic (AAMAS, 2024)

Semifactual Explanations for Reinforcement Learning. - Jasmina Gajcin; Jovan Jeromela; Ivana Dusparic (HAI, 2024)

ACTER: Diverse and Actionable Counterfactual Sequences for Explaining and Diagnosing RL Policies. - Jasmina Gajcin; Ivana Dusparic (CoRR, 2024)

Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities. - Jasmina Gajcin; Ivana Dusparic (ACM Comput. Surv., 2024)

Towards Personalised and User-Friendly Counterfactual Sequences for Failure Correction. - Jasmina Gajcin; Jovan Jeromela; Ivana Dusparic (UMAP (Adjunct Publication), 2025)

Agentic AI Needs a Systems Theory. - Erik Miehling; Karthikeyan Natesan Ramamurthy; Kush R. Varshney; Matthew Riemer; Djallel Bouneffouf 001; John T. Richards; Amit Dhurandhar; Elizabeth M. Daly; Michael Hind; Prasanna Sattigeri; Dennis Wei; Ambrish Rawat; et al. (CoRR, 2025)