Metric Hedonic Games on the Line

Merlin de la Haye, Pascal Lenzner, Farehe Soheil, Marcus Wunderlich
2/5/2026
cs.GTcs.AI

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Abstract

Hedonic games are fundamental models for investigating the formation of coalitions among a set of strategic agents, where every agent has a certain utility for every possible coalition of agents it can be part of. To avoid the intractability of defining exponentially many utilities for all possible coalitions, many variants with succinct representations of the agents' utility functions have been devised and analyzed, e.g., modified fractional hedonic games by Monaco et al. [JAAMAS 2020]. We extend this by studying a novel succinct variant that is related to modified fractional hedonic games. In our model, each agent has a fixed type-value and an agent's cost for some given coalition is based on the differences between its value and those of the other members of its coalition. This allows to model natural situations like athletes forming training groups with similar performance levels or voters that partition themselves along a political spectrum. In particular, we investigate natural variants where an agent's cost is defined by distance thresholds, or by the maximum or average value difference to the other agents in its coalition. For these settings, we study the existence of stable coalition structures, their properties, and their quality in terms of the price of anarchy and the price of stability. Further, we investigate the impact of limiting the maximum number of coalitions. Despite the simple setting with metric distances on a line, we uncover a rich landscape of models, partially with counter-intuitive behavior. Also, our focus on both swap stability and jump stability allows us to study the influence of fixing the number and the size of the coalitions. Overall, we find that stable coalition structures always exist but that their properties and quality can vary widely.

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Cite this paper

@article{haye2026metric,
  title  = {Metric Hedonic Games on the Line},
  author = {Merlin de la Haye and Pascal Lenzner and Farehe Soheil and Marcus Wunderlich},
  year   = {2026},
  eprint = {2602.05888},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2602.05888v2}
}

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