This schedule is tentative and subject to change. All times are in CET (Central European Time).
- 12/4: Deadline for seminar registration. Interested students should register through https://seminars.cs.uni-saarland.de/.
- 20/4 (10:15 – 12:00): Introduction to the seminar course and the first tutoring session.
- 4/5 (10:30 – 12:00): Office hours.
- 9/5 (14:00): Deadline for submitting the reports and presentation slides for the papers in the first batch.
- 11/5 (10:15 – 12:00): Presentation and discussion session for the papers in the first batch.
- A Modification of the Halpern-Pearl Definition of Causality
by Joseph Y. Halpern, at IJCAI 2015 - Towards Formal Definitions of Blameworthiness, Intention, and Moral Responsibility
by Joseph Y. Halpern and Max Kleiman-Weiner, at AAAI 2018 - Designing Accountable Systems
by Severin Kacianka and Alexander Pretschner, at FAccT 2021
- A Modification of the Halpern-Pearl Definition of Causality
- 25/5 (10:15 – 12:00): The second tutoring session.
- 9/6 (10:30 – 12:00): Office hours.
- 13/6 (14:00): Deadline for submitting the reports and presentation slides for the first two papers in the second batch.
- 15/6 (10:15 – 12:00): Presentation and discussion session for the first two papers in the second batch.
- Fairness in Decision-Making — The Causal Explanation Formula
by Junzhe Zhang and Elias Bareinboim, at AAAI 2018 - Agent Incentives: A Causal Perspective
by Tom Everitt, Ryan Carey, Eric D. Langlois, Pedro A. Ortega and Shane Legg, at AAAI 2021
- Fairness in Decision-Making — The Causal Explanation Formula
- 20/6 (14:00): Deadline for submitting the reports and presentation slides for the last two papers in the second batch.
- 22/6 (10:15 – 12:00): Presentation and discussion session for the last two papers in the second batch.
- Counterfactual Harm
by Jonathan G. Richens, Rory Beard and Daniel H. Thompson, at NeurIPS 2022 - Causal structure-based root cause analysis of outliers
by Kailash Budhathoki, Lenon Minorics, Patrick Blöbaum and Dominik Janzing, at ICML 2022
- Counterfactual Harm
- 29/6 (10:15 – 12:00): The third tutoring session.
- 13/7 (10:30 – 12:00): Office hours.
- 18/7 (14:00): Deadline for submitting the reports and presentation slides for the papers in the third batch.
- 20/7 (10:15 – 12:00): Presentation and discussion session for papers in the third batch.
- Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes
by Stelios Triantafyllou, Adish Singla and Goran Radanovic, at AIES 2022 - Explainable Reinforcement Learning Through a Causal Lens
by Prashan Madumal, Tim Miller, Liz Sonenberg and Frank Vetere, at AAAI 2020 - Path-Specific Objectives for Safer Agent Incentives
by Sebastian Farquhar, Ryan Carey and Tom Everitt, at AAAI 2022
- Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes
Complete Reading List
1st Batch: Actual causality and responsibility attribution
- A Modification of the Halpern-Pearl Definition of Causality
by Joseph Y. Halpern, at IJCAI 2015 - Towards Formal Definitions of Blameworthiness, Intention, and Moral Responsibility
by Joseph Y. Halpern and Max Kleiman-Weiner, at AAAI 2018 - Designing Accountable Systems
by Severin Kacianka and Alexander Pretschner, at FAccT 2021
2nd Batch: Explainability and agent incentives
- Fairness in Decision-Making — The Causal Explanation Formula
by Junzhe Zhang and Elias Bareinboim, at AAAI 2018 - Agent Incentives: A Causal Perspective
by Tom Everitt, Ryan Carey, Eric D. Langlois, Pedro A. Ortega and Shane Legg, at AAAI 2021 - Counterfactual Harm
by Jonathan G. Richens, Rory Beard and Daniel H. Thompson, at NeurIPS 2022 - Causal structure-based root cause analysis of outliers
by Kailash Budhathoki, Lenon Minorics, Patrick Blöbaum and Dominik Janzing, at ICML 2022
3rd Batch: Accountability in Reinforcement Learning
- Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes
by Stelios Triantafyllou, Adish Singla and Goran Radanovic, at AIES 2022 - Explainable Reinforcement Learning Through a Causal Lens
by Prashan Madumal, Tim Miller, Liz Sonenberg and Frank Vetere, at AAAI 2020 - Path-Specific Objectives for Safer Agent Incentives
by Sebastian Farquhar, Ryan Carey and Tom Everitt, at AAAI 2022