A game-theoretic account of responsibility allocation

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributed

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 languageEnglish
Title of host publicationProceedings of the Thirtieth International Joint Conference on Artificial Intelligence
EditorsZhi-Hua Zhou
PublisherInternational Joint Conferences on Artificial Intelligence
Pages1773-1779
Number of pages7
ISBN (electronic)978-0-9992411-9-6
Publication statusPublished - 1 Aug 2021
Peer-reviewedNo

External IDs

Scopus 85108134730
ORCID /0000-0002-5321-9343/work/142236781

Keywords