Visualizing Coalition Formation: From Hedonic Games to Image Segmentation

Pedro Henrique de Paula Franca, Lucas Lopes Felipe, Daniel Sadoc Menasche

Keywords: Image segmentation, Hedonic games, Community detection, Graph-based segmentation

TL;DR: Image segmentation provides a visual lens for hedonic coalition formation, revealing resolution-driven regime transitions and separating intrinsic failures from recomposition artifacts.

Abstract: 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.

Track: Short Paper

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Submission Number: 41