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JAAMAS 2020

Computing and testing Pareto optimal committees

Journal Article OriginalPaper Artificial Intelligence · Multi-Agent Systems

Abstract

Abstract Selecting a set of alternatives based on the preferences of agents is an important problem in committee selection and beyond. Among the various criteria put forth for desirability of a committee, Pareto optimality is a minimal and important requirement. As asking agents to specify their preferences over exponentially many subsets of alternatives is practically infeasible, we assume that each agent specifies a weak order on single alternatives, from which a preference relation over subsets is derived using some preference extension. We consider five prominent extensions (responsive, downward lexicographic, upward lexicographic, best, and worst). For each of them, we consider the corresponding Pareto optimality notion, and we study the complexity of computing and verifying Pareto optimal outcomes. For each of the preference extensions, we give a complete characterization of the complexity of testing Pareto optimality when preferences are dichotomous or linear. We also consider strategic issues: for four of the set extensions, we present a linear-time, Pareto optimal and strategyproof algorithm that even works for weak preferences.

Authors

Keywords

  • Committee selection
  • Multiwinner voting
  • Pareto optimality
  • Algorithms and complexity
  • Set extensions
  • C70
  • D61
  • D71

Context

Venue
Autonomous Agents and Multi-Agent Systems
Archive span
2005-2026
Indexed papers
940
Paper id
510094481628907512
v2026.09.13