Abstract
A well-studied trait of human reasoning and decision-making is the ability to not only make decisions in the presence of contradictions, but also to explain why a decision was made, in particular if a decision deviates from what is expected by an inquirer who requests the explanation. In this paper, we examine this phenomenon, which has been extensively explored by behavioral economics research, from the perspective of symbolic artificial intelligence. In particular, we introduce four levels of intelligent reasoning in face of contradictions, which we motivate from a microeconomics and behavioral economics perspective. We relate these principles to symbolic reasoning approaches, using abstract argumentation as an exemplary method. This allows us to ground the four levels in a body of related previous and ongoing research, which we use as a point of departure for outlining future research directions.
Original language | English |
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Title of host publication | Explainable and Transparent AI and Multi-Agent Systems - 3rd International Workshop, EXTRAAMAS 2021, Revised Selected Papers |
Editors | Davide Calvaresi, Amro Najjar, Michael Winikoff, Kary Främling |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 280-295 |
Number of pages | 16 |
ISBN (Print) | 9783030820169 |
DOIs | |
State | Published - 2021 |
Event | 3rd International Workshop on Explainable, Transparent AI and Multi-Agent Systems, EXTRAAMAS 2021 - Virtual, Online Duration: 3 May 2021 → 7 May 2021 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12688 LNAI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 3rd International Workshop on Explainable, Transparent AI and Multi-Agent Systems, EXTRAAMAS 2021 |
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City | Virtual, Online |
Period | 3/05/21 → 7/05/21 |
Bibliographical note
Publisher Copyright:© 2021, Springer Nature Switzerland AG.
Funding
Acknowledgments. The authors thank Amro Najjar, Michele Persiani, and the anonymous reviewers for their useful feedback. This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.
Funders | Funder number |
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Knut och Alice Wallenbergs Stiftelse |
Keywords
- Explainable artificial intelligence
- Non-monotonic reasoning
- Symbolic artificial intelligence