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AIJ 2009

Ranking games

Journal Article journal-article Artificial Intelligence

Abstract

The outcomes of many strategic situations such as parlor games or competitive economic scenarios are rankings of the participants, with higher ranks generally at least as desirable as lower ranks. Here we define ranking games as a class of n-player normal-form games with a payoff structure reflecting the players' von Neumann–Morgenstern preferences over their individual ranks. We investigate the computational complexity of a variety of common game-theoretic solution concepts in ranking games and deliver hardness results for iterated weak dominance and mixed Nash equilibrium when there are more than two players, and for pure Nash equilibrium when the number of players is unbounded but the game is described succinctly. This dashes hope that multi-player ranking games can be solved efficiently, despite their profound structural restrictions. Based on these findings, we provide matching upper and lower bounds for three comparative ratios, each of which relates two different solution concepts: the price of cautiousness, the mediation value, and the enforcement value.

Authors

Keywords

  • Multi-agent systems
  • Game theory
  • Strict competitiveness
  • n-player games
  • Solution concepts
  • Computational complexity

Context

Venue
Artificial Intelligence
Archive span
1970-2026
Indexed papers
3976
Paper id
984535257544199325