A game-theoretic account of responsibility allocation

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragen

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

OriginalspracheEnglisch
TitelProceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021
Redakteure/-innenZhi-Hua Zhou
Herausgeber (Verlag)International Joint Conferences on Artificial Intelligence
Seiten1773-1779
Seitenumfang7
ISBN (elektronisch)978-0-9992411-9-6
PublikationsstatusVeröffentlicht - 1 Aug. 2021
Peer-Review-StatusNein

Externe IDs

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

Schlagworte

ASJC Scopus Sachgebiete