Explainable Shapley-Based Allocation (Student Abstract)

Meir Nizri, Noam Hazon, Amos Azaria

نتاج البحث: فصل من :كتاب / تقرير / مؤتمرمنشور من مؤتمرمراجعة النظراء


The Shapley value is one of the most important normative division scheme in cooperative game theory, satisfying basic axioms. However, some allocation according to the Shapley value may seem unfair to humans. In this paper, we develop an automatic method that generates intuitive explanations for a Shapley-based payoff allocation, which utilizes the basic axioms. Given a coalitional game, our method decomposes it to sub-games, for which it is easy to generate verbal explanations, and shows that the given game is composed of the sub-games. Since the payoff allocation for each sub-game is perceived as fair, the Shapley-based payoff allocation for the given game should seem fair as well. We run an experiment with 210 human participants and show that when applying our method, humans perceive Shapley-based payoff allocation as significantly more fair than when using a general standard explanation.

اللغة الأصليةالإنجليزيّة
عنوان منشور المضيفIAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations
ناشرAssociation for the Advancement of Artificial Intelligence
عدد الصفحات2
رقم المعيار الدولي للكتب (الإلكتروني)1577358767, 9781577358763
حالة النشرنُشِر - 30 يونيو 2022
الحدث36th AAAI Conference on Artificial Intelligence, AAAI 2022 - Virtual, Online
المدة: ٢٢ فبراير ٢٠٢٢١ مارس ٢٠٢٢

سلسلة المنشورات

الاسمProceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022
مستوى الصوت36


!!Conference36th AAAI Conference on Artificial Intelligence, AAAI 2022
المدينةVirtual, Online

All Science Journal Classification (ASJC) codes

  • !!Artificial Intelligence


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