# Visualizing Coalition Formation: From Hedonic Games to Image Segmentation

arXiv: https://arxiv.org/abs/2603.07890 · HTML: https://mlsanity.com/paper/2603.07890/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 13 references that are in the map.
- First posted on arXiv 9 Mar 2026.

## Builds on (most cited first, 1 of 1)

- [From Leiden to Pleasure Island: The Constant Potts Model for Community Detection as a Hedonic Game](https://mlsanity.com/paper/2509.03834/) (2025)

## Abstract (arXiv)

We propose image segmentation as a visual diagnostic testbed for coalition formation in hedonic games. Modeling pixels as agents on a graph, we study how a granularization parameter shapes equilibrium fragmentation and boundary structure. On the Weizmann single-object benchmark, we relate multi-coalition equilibria to binary protocols by measuring whether the converged coalitions overlap with a foreground ground-truth. We observe transitions from cohesive to fragmented yet recoverable equilibria, and finally to intrinsic failure under excessive fragmentation. Our core contribution links multi-agent systems with image segmentation by quantifying the impact of mechanism design parameters on equilibrium structures.