Learning Hedonic Games

Learning Hedonic Games

Jakub Sliwinski, Yair Zick

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Main track. Pages 2730-2736. https://doi.org/10.24963/ijcai.2017/380

Coalitional stability in hedonic games has usually been considered in the setting where agent preferences are fully known. We consider the setting where agent preferences are unknown; we lay the theoretical foundations for studying the interplay between coalitional stability and (PAC) learning in hedonic games. We introduce the notion of PAC stability - the equivalent of core stability under uncertainty - and examine the PAC stabilizability and learnability of several popular classes of hedonic games.
Keywords:
Machine Learning: Learning Preferences or Rankings
Agent-based and Multi-agent Systems: Cooperative Games