Hedonic Clustering Games

Feldman, Moran; Lewin-Eytan, Liane; Naor, Joseph

doi:10.1145/2742345

Cited by 40 publications

(32 citation statements)

References 23 publications

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“…Peters and Elkind (2015) consider several classes of hedonic games and identify simple conditions that are sufficient for the problem of checking whether a given game admits a stable outcome to be computationally hard. Feldman et al (2012) characterize Nash stable coalition structures in some interesting subclasses of hedonic games. It is worth noticing that their model is quite different from the one considered in this paper: they do not have an underlying graph, but players lie in a metric space with a distance function modeling their distance or "similarity".…”

Section: Related Workmentioning

confidence: 99%

“…They further prove that the price of stability is 1 for the variant of Olsen (2012), still for general unweighted graphs. Feldman et al (2012) investigate some interesting subclasses of hedonic games (however, as aforementioned, their model is quite different from the one considered in this paper) and provide bounds on the efficiency loss of Nash stable outcomes.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, it is k-Strong Nash stable if no subset of at most k agents can cooperatively deviate so as to induce a benefit to all of its members. There are also examples of studies on Nash stability in hedonic games, in which self-organized coalition structures are obtained from the decisions taken by independent and selfish agents (Bloch & Diamantoudi, 2011;Feldman, Lewin-Eytan, & Naor, 2012;Gairing & Savani, 2010).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Nash Stable Outcomes in Fractional Hedonic Games: Existence, Efficiency and Computation

Bilò¹,

Fanelli²,

Flammini³

et al. 2018

jair

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We consider fractional hedonic games, a subclass of coalition formation games that can be succinctly modeled by means of a graph in which nodes represent agents and edge weights the degree of preference of the corresponding endpoints. The happiness or utility of an agent for being in a coalition is the average value she ascribes to its members. We adopt Nash stable outcomes as the target solution concept; that is we focus on states in which no agent can improve her utility by unilaterally changing her own group. We provide existence, efficiency and complexity results for games played on both general and specific graph topologies. As to the efficiency results, we mainly study the quality of the best Nash stable outcome and refer to the ratio between the social welfare of an optimal coalition structure and the one of such an equilibrium as to the price of stability. In this respect, we remark that a best Nash stable outcome has a natural meaning of stability, since it is the optimal solution among the ones which can be accepted by selfish agents. We provide upper and lower bounds on the price of stability for different topologies, both in case of weighted and unweighted edges. Beside the results for general graphs, we give refined bounds for various specific cases, such as triangle-free, bipartite graphs and tree graphs. For these families, we also show how to efficiently compute Nash stable outcomes with provable good social welfare.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nash Stable Outcomes in Fractional Hedonic Games: Existence, Efficiency and Computation

Bilò¹,

Fanelli²,

Flammini³

et al. 2018

jair

View full text Add to dashboard Cite

show abstract

“…The earliest and most well-known result in the area is the one on stable marriages by Gale and Shapley (Gale and Shapley 1962). Further works include (Aumann and Dreze 1974;Apt et al 2014;Banerjee, Konishi, and Sonmez 2001;Bogomolnaia and Jackson 2002;Chalkiadakis et al 2009;Feldman, Lewin-Eytan, and Naor 2012;Greenberg and Weber 1993;Hajdukova 2006;Hart and Kurz 1983;Immorlica, Markakis, and Piliouras 2010;Yi 1997).…”

Section: Related Workmentioning

confidence: 99%

You Get What You Share: Incentives for a Sharing Economy

Gollapudi

Kollias

Panigrahi

2019

AAAI

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In recent years, a range of online applications have facilitated resource sharing among users, resulting in a significant increase in resource utilization. In all such applications, sharing one’s resources or skills with other agents increases social welfare. In general, each agent will look for other agents whose available resources complement hers, thereby forming natural sharing groups. In this paper, we study settings where a large population self-organizes into sharing groups. In many cases, centralized optimization approaches for creating an optimal partition of the user population are infeasible because either the central authority does not have the necessary information to compute an optimal partition, or it does not have the power to enforce a partition. Instead, the central authority puts in place an incentive structure in the form of a utility sharing method, before letting the participants form the sharing groups by themselves. We first analyze a simple equal-sharing method, which is the one most typically encountered in practice and show that it can lead to highly inefficient equilibria. We then propose a Shapley-sharing method and show that it significantly improves overall social welfare.

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“…Kleinberg and Oren [14] define a project selection game with decreasing player payoff functions, unlike ours which may not be monotone, and their results focus on redesigning project payoff functions to ensure that the optimal solution is stable. Finally, Feldman et al [9] define a class of non-cooperative games called hedonic clustering games, and provide quality of equilibrium results for them. Their model has little in common with ours, but they borrow heavily from hedonic games literature and apply concepts like price of anarchy, as we do.…”

Section: Related Workmentioning

confidence: 99%

Profit Sharing with Thresholds and Non-monotone Player Utilities

Anshelevich

Postl

2016

Theory Comput Syst

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We study profit sharing games in which players select projects to participate in and share the reward resulting from that project equally. Unlike most existing work, in which it is assumed that the player utility is monotone in the number of participants working on their project, we consider non-monotone player utilities. Such utilities could result, for example, from "threshold" or "phase transition" effects, when the total benefit from a project improves slowly until the number of participants reaches some critical mass, then improves rapidly, and then slows again due to diminishing returns.Non-monotone player utilities result in a lot of instability: strong Nash equilibrium may no longer exist, and the quality of Nash equilibria may be far away from the centralized optimum. We show, however, that by adding additional requirements such as players needing permission to leave a project from the players currently on this project, or instead players needing permission to a join a project from players on that project, we ensure that strong Nash equilibrium always exists. Moreover, just the addition of permission to leave already guarantees the existence of strong Nash equilibrium within a factor of 2 of the social optimum. In this paper, we provide results on the existence and quality of several different coalitional solution concepts, focusing especially on permission to leave and join projects, and show that such requirements result in the existence of good stable solutions even for the case when player utilities are non-monotone.

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Hedonic Clustering Games

Cited by 40 publications

References 23 publications

Nash Stable Outcomes in Fractional Hedonic Games: Existence, Efficiency and Computation

Nash Stable Outcomes in Fractional Hedonic Games: Existence, Efficiency and Computation

You Get What You Share: Incentives for a Sharing Economy

Profit Sharing with Thresholds and Non-monotone Player Utilities

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