Arrow Research search
Back to IJCAI

IJCAI 2018

Accountable Approval Sorting

Conference Paper Agent-based and Multi-agent Systems Artificial Intelligence

Abstract

We consider decision situations in which a set of points of view (voters, criteria) are to sort a set of candidates to ordered categories (Good/Bad). Candidates are judged good, when approved by a sufficient set of points of view; this corresponds to NonCompensatory Sorting. To be accountable, such approval sorting should provide guarantees about the decision process and decisions concerning specific candidates. We formalize accountability using a feasibility problem expressed as a boolean satisfiability formulation. We illustrate different forms of accountability when a committee decides with approval sorting and study the information that should be disclosed by the committee.

Authors

Keywords

  • Agent-based and Multi-agent Systems: Voting
  • Constraints and SAT: Modeling; Formulation
  • Knowledge Representation and Reasoning: Preference Modelling and Preference-Based Reasoning

Context

Venue
International Joint Conference on Artificial Intelligence
Archive span
1969-2025
Indexed papers
14525
Paper id
781174642125947640
v2026.09.13