A game-theoretic account of responsibility allocation
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Contributors
Abstract
When designing or analyzing multi-agent systems, a fundamental problem is responsibility ascription: to specify which agents are responsible for the joint outcome of their behaviors and to which extent. We model strategic multi-agent interaction as an extensive form game of imperfect information and define notions of forward (prospective) and backward (retrospective) responsibility. Forward responsibility identifies the responsibility of a group of agents for an outcome along all possible plays, whereas backward responsibility identifies the responsibility along a given play. We further distinguish between strategic and causal backward responsibility, where the former captures the epistemic knowledge of players along a play, while the latter formalizes which players – possibly unknowingly – caused the outcome. A formal connection between forward and backward notions is established in the case of perfect recall. We further ascribe quantitative responsibility through cooperative game theory. We show through a number of examples that our approach encompasses several prior formal accounts of responsibility attribution.
Details
Original language | English |
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Title of host publication | Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 |
Editors | Zhi-Hua Zhou |
Publisher | International Joint Conferences on Artificial Intelligence |
Pages | 1773-1779 |
Number of pages | 7 |
ISBN (electronic) | 978-0-9992411-9-6 |
Publication status | Published - 1 Aug 2021 |
Peer-reviewed | No |
External IDs
Scopus | 85108134730 |
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ORCID | /0000-0002-5321-9343/work/142236781 |