Two’s Company, Three’s a Crowd: Consensus-Halving for a Constant Number of Agents

Argyrios Deligkas, Aris Filos-Ratsikas, Alexandros Hollender

Research output: Contribution to journalArticlepeer-review

Abstract

We consider the ε-Consensus-Halving problem, in which a set of heterogeneous agents aim at dividing a continuous resource into two (not necessarily contiguous) portions that all of them simultaneously consider to be of approximately the same value (up to ε). This problem was recently shown to be PPA-complete, for n agents and n cuts, even for very simple valuation functions. In a quest to understand the root of the complexity of the problem, we consider the setting where there is only a constant number of agents, and we consider both the computational complexity and the query complexity of the problem. For agents with monotone valuation functions, we show a dichotomy: for two agents the problem is polynomial-time solvable, whereas for three or more agents it becomes PPA-complete. Similarly, we show that for two monotone agents the problem can be solved with polynomially-many queries, whereas for three or more agents, we provide exponential query complexity lower bounds. These results are enabled via an interesting connection to a monotone Borsuk-Ulam problem, which may be of independent interest. For agents with general valuations, we show that the problem is PPA-complete and admits exponential query complexity lower bounds, even for two agents.
Original languageEnglish
Article number103784
Number of pages39
JournalArtificial Intelligence Journal
Volume313
Early online date9 Sep 2022
DOIs
Publication statusPublished - 1 Dec 2022

Keywords

  • Consensus-halving
  • Fair division
  • Computational complexity
  • Query complexity
  • Robertson-Webb

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