English

Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries

Artificial Intelligence 2023-08-01 v1 Databases Logic in Computer Science

Abstract

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., \mlangprefψ1ψ2A\mlangpref{\psi_1}{\psi_2}{A} (read loosely as the set of outcomes satisfying ψ1\psi_1 that are preferred over outcomes satisfying ψ2\psi_2 by a set of stakeholders AA). 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\mu-calculus. We present experimental results that demonstrate the feasibility of our approach.

Keywords

Cite

@article{arxiv.2307.16307,
  title  = {Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries},
  author = {Samik Basu and Vasant Honavar and Ganesh Ram Santhanam and Jia Tao},
  journal= {arXiv preprint arXiv:2307.16307},
  year   = {2023}
}

Comments

A shorter version is published in the proceeding of 26th European Conference on Artificial Intelligence ECAI 2023

R2 v1 2026-06-28T11:43:55.102Z