TY - GEN
T1 - Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries
AU - Basu, Samik
AU - Honavar, Vasant
AU - Santhanam, Ganesh Ram
AU - Tao, Jia
N1 - Publisher Copyright:
© 2023 The Authors.
PY - 2023/9/28
Y1 - 2023/9/28
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85175876307&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85175876307&partnerID=8YFLogxK
U2 - 10.3233/FAIA230272
DO - 10.3233/FAIA230272
M3 - Conference contribution
AN - SCOPUS:85175876307
T3 - Frontiers in Artificial Intelligence and Applications
SP - 206
EP - 213
BT - ECAI 2023 - 26th European Conference on Artificial Intelligence, including 12th Conference on Prestigious Applications of Intelligent Systems, PAIS 2023 - Proceedings
A2 - Gal, Kobi
A2 - Gal, Kobi
A2 - Nowe, Ann
A2 - Nalepa, Grzegorz J.
A2 - Fairstein, Roy
A2 - Radulescu, Roxana
PB - IOS Press BV
T2 - 26th European Conference on Artificial Intelligence, ECAI 2023
Y2 - 30 September 2023 through 4 October 2023
ER -