Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries

Samik Basu, Vasant Honavar, Ganesh Ram Santhanam, Jia Tao

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Many decision-making scenarios, e.g., public policy, healthcare, business, and disaster response, require accommodating the preferences of multiple stakeholders. We offer the first formal treatment of reasoning with multi-stakeholder qualitative preferences in a setting where stakeholders express their preferences in a qualitative preference language, e.g., CP-net, CI-net, TCP-net, CP-Theory. We introduce a query language for expressing queries against such preferences over sets of outcomes that satisfy specified criteria, e.g., ψ1PAψ2 (read loosely as the set of outcomes satisfying ψ1 that are preferred over outcomes satisfying ψ2 by a set of stakeholders A). Motivated by practical application scenarios, we introduce and analyze several alternative semantics for such queries, and examine their interrelationships. We provide a provably correct algorithm for answering multi-stakeholder qualitative preference queries using model checking in alternation-free μ-calculus. We present experimental results that demonstrate the feasibility of our approach.

Original languageEnglish (US)
Title of host publicationECAI 2023 - 26th European Conference on Artificial Intelligence, including 12th Conference on Prestigious Applications of Intelligent Systems, PAIS 2023 - Proceedings
EditorsKobi Gal, Kobi Gal, Ann Nowe, Grzegorz J. Nalepa, Roy Fairstein, Roxana Radulescu
PublisherIOS Press BV
Number of pages8
ISBN (Electronic)9781643684369
StatePublished - Sep 28 2023
Event26th European Conference on Artificial Intelligence, ECAI 2023 - Krakow, Poland
Duration: Sep 30 2023Oct 4 2023

Publication series

NameFrontiers in Artificial Intelligence and Applications
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314


Conference26th European Conference on Artificial Intelligence, ECAI 2023

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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