Learning Cooperative Solution Concepts from Voting Behavior: A Case Study on the Israeli Knesset

Omer Lev, Wei Lu, Alan Tsang, Yair Zick

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Most frameworks for computing solution concepts in hedonic games are theoretical in nature, and require complete knowledge of all agent preferences, an impractical assumption in real-world settings. This paper presents the first application of strategic hedonic game models on real-world data. We show that PAC stable solutions can reflect Members of Knesset’ political positions and reveal politicians who are known to deviate from party lines. Moreover, these models compare favorably to machine learning models
Original languageEnglish
Title of host publicationProceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems
Pages1572-1574
Number of pages3
StatePublished - 2021

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