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  An Axiomatic Approach to Formalized Responsibility Ascription

Hiller, S., Isreal, J., Heitzig, J. (2022): An Axiomatic Approach to Formalized Responsibility Ascription. - In: Aydoğan, R., Criado, N., Lang, J., Sanchez-Anguix, V., Serramia, M. (Eds.), PRIMA 2022: Principles and Practice of Multi-Agent Systems, (Lecture Notes in Computer Science ; 13753), Cham : Springer, 435-457.
https://doi.org/10.1007/978-3-031-21203-1_26

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Datensatz-Permalink: https://publications.pik-potsdam.de/pubman/item/item_27425 Versions-Permalink: https://publications.pik-potsdam.de/pubman/item/item_27425_1
Genre: Buchkapitel

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Urheber

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 Urheber:
Hiller, Sarah1, Autor              
Isreal, Jonas2, Autor
Heitzig, Jobst1, Autor              
Affiliations:
1Potsdam Institute for Climate Impact Research, Potsdam, ou_persistent13              
2External Organizations, ou_persistent22              

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Schlagwörter: -
 Zusammenfassung: A formalized and quantifiable responsibility score is a crucial component in many aspects of the development and application of multi-agent systems and autonomous agents. We can employ it to inform decision making processes based on ethical considerations, as a measure to ensure redundancy that helps us in avoiding system failure, as well as for verifying that autonomous systems remain trustworthy by testing for unwanted responsibility voids in advance. We follow recent proposals to use probabilities as the basis for responsibility ascription in uncertain environments rather than the deterministic causal views employed in much of the previous formal philosophical literature. Using an axiomatic approach we formally evaluate the qualities of (classes of) proposed responsibility functions. To this end, we decompose the computation of the responsibility a group carries for an outcome into the computation of values that we assign to its members for individual decisions leading to that outcome, paired with an appropriate aggregation function. Next, we discuss a number of intuitively desirable properties for each of these contributing functions. We find an incompatibility between axioms determining upper and lower bounds for the values assigned at the member level. Regarding the aggregation from member-level values to group-level responsibility we are able to axiomatically characterise one promising aggregation function. Finally, we present two maximally axiom compliant group-level responsibility measures – one respecting the lower bound axioms at the member level and one respecting the corresponding upper bound axioms.

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Sprache(n): eng - Englisch
 Datum: 2022-09-202022-11-122022-11-12
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: Organisational keyword: RD4 - Complexity Science
PIKDOMAIN: RD4 - Complexity Science
Working Group: FutureLab on Game Theory and Networks of Interacting Agents
Model / method: Game Theory
Regional keyword: Global
Research topic keyword: Climate Policy
Research topic keyword: Economics
Research topic keyword: Global Commons
Research topic keyword: Inequality and Equity
MDB-ID: No data to archive
DOI: 10.1007/978-3-031-21203-1_26
 Art des Abschluß: -

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Projektinformation

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Projektname : the Berlin Mathematics Research Center MATH+ (EXC-2046/1)
Grant ID : 390685689
Förderprogramm : Germany’s Excellence Strategy
Förderorganisation : Deutsche Forschungsgemeinschaft
Projektname : -
Grant ID : BR 4744/2-1
Förderprogramm : -
Förderorganisation : -

Quelle 1

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Titel: PRIMA 2022: Principles and Practice of Multi-Agent Systems
Genre der Quelle: Buch
 Urheber:
Aydoğan, Reyhan1, Herausgeber
Criado, Natalia1, Herausgeber
Lang, Jérôme1, Herausgeber
Sanchez-Anguix, Victor1, Herausgeber
Serramia, Marc1, Herausgeber
Affiliations:
1 External Organizations, ou_persistent22            
Ort, Verlag, Ausgabe: Cham : Springer
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 435 - 457 Identifikator: ISBN: 978-3-031-21203-1

Quelle 2

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Titel: Lecture Notes in Computer Science
Genre der Quelle: Reihe
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 13753 Artikelnummer: - Start- / Endseite: - Identifikator: -