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Simple priorities and core stability in hedonic games

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In this paper, the authors study hedonic games where each player views every other player either as a friend or as an enemy, and propose two simple priority criteria for comparison of coalitions and the corresponding preference restrictions based on appreciation of friends and aversion to enemies.
Abstract
In this paper we study hedonic games where each player views every other player either as a friend or as an enemy. Two simple priority criteria for comparison of coalitions are suggested, and the corresponding preference restrictions based on appreciation of friends and aversion to enemies are considered. We characterize internally stable coalitions on the proposed domains and show how these characterizations can be used for generating a strict core element in the first case and a core element in the second case. Moreover, we prove that an element of the strict core under friends appreciation can be found in polynomial time, while finding an element of the core under enemies aversion is NP-hard.

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Computational Aspects of Cooperative Game Theory

TL;DR: This talk introduces basic concepts from cooperative game theory, and in particular the key solution concepts: the core and the Shapley value, and introduces the key issues that arise if one is to consider the cooperative games in a computational setting.
Proceedings Article

Hedonic coalition nets

TL;DR: Hedonic coalition nets are shown to be universally expressive, yet are at least as succinct as other existing representation schemes for hedonic games, and the complexity of many natural decision problems for these games are investigated.
Journal ArticleDOI

Computing desirable partitions in additively separable hedonic games

TL;DR: In this paper, the authors consider a number of solution concepts from cooperative game theory, welfare theory, and social choice theory as criteria for desirable partitions in additively separable hedonic games.
Posted Content

Fractional Hedonic Games

TL;DR: In this article, the authors formalized fractional hedonic games, a class of coalition formation games in which the utility of a player is the average value he ascribes to the members of his coalition.
Proceedings ArticleDOI

Fractional hedonic games

TL;DR: In this article, the utility of a player in a coalition structure is the average value he ascribes to the members of his coalition, and a number of conditions under which the core of fractional hedonic games is non-empty and algorithms for computing a core stable outcome are proposed.
References
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Journal ArticleDOI

Depth-First Search and Linear Graph Algorithms

TL;DR: The value of depth-first search or “backtracking” as a technique for solving problems is illustrated by two examples of an improved version of an algorithm for finding the strongly connected components of a directed graph.
Journal ArticleDOI

The Stability of Hedonic Coalition Structures

TL;DR: This work considers the partitioning of a society into coalitions in purely hedonic settings, and shows that if coalitions can be ordered according to some characteristic over which players have single-peaked preferences, then there exists an individually stable coalition partition.
Journal ArticleDOI

The Core of an N Person Game

Herbert E. Scarf
- 01 Jan 1967 - 
TL;DR: In this paper, the core of the n-person game is defined as those utility vectors which are feasible for the entire group of players and which can be blocked by no coalition.
Journal ArticleDOI

Core in a Simple Coalition Formation Game

TL;DR: The core of a class of coalition formation game in which every player's payoff depends only on the members of her coalition is analyzed, and two top-coalition properties each of which guarantee the existence of a core allocation are introduced.
Journal ArticleDOI

Hedonic coalitions: optimality and stability

Jacques H. Dreze
- 01 May 1980 - 
TL;DR: In this paper, the authors studied the stability of coalitions in a cooperative game with hedonic coalitions and showed that transfers among coalitions may be necessary to attain Pareto optimality.
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