联盟形成的可视化:从享乐博弈到图像分割 / Visualizing Coalition Formation: From Hedonic Games to Image Segmentation
1️⃣ 一句话总结
这篇论文将图像分割作为可视化工具,用于研究享乐博弈中智能体如何形成联盟,并通过量化机制设计参数揭示了从紧密联盟到过度碎片化失效的转变过程。
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.
联盟形成的可视化:从享乐博弈到图像分割 / Visualizing Coalition Formation: From Hedonic Games to Image Segmentation
这篇论文将图像分割作为可视化工具,用于研究享乐博弈中智能体如何形成联盟,并通过量化机制设计参数揭示了从紧密联盟到过度碎片化失效的转变过程。
源自 arXiv: 2603.07890