Topological influence and locality in swap schelling games
-
Published:2022-08-16
Issue:2
Volume:36
Page:
-
ISSN:1387-2532
-
Container-title:Autonomous Agents and Multi-Agent Systems
-
language:en
-
Short-container-title:Auton Agent Multi-Agent Syst
Author:
Bilò Davide, Bilò Vittorio, Lenzner Pascal, Molitor LouiseORCID
Abstract
AbstractResidential segregation is a wide-spread phenomenon that can be observed in almost every major city. In these urban areas residents with different racial or socioeconomic background tend to form homogeneous clusters. Schelling’s famous agent-based model for residential segregation explains how such clusters can form even if all agents are tolerant, i.e., if they agree to live in mixed neighborhoods. For segregation to occur, all it needs is a slight bias towards agents preferring similar neighbors. Very recently, Schelling’s model has been investigated from a game-theoretic point of view with selfish agents that strategically select their residential location. In these games, agents can improve on their current location by performing a location swap with another agent who is willing to swap. We significantly deepen these investigations by studying the influence of the underlying topology modeling the residential area on the existence of equilibria, the Price of Anarchy and on the dynamic properties of the resulting strategic multi-agent system. Moreover, as a new conceptual contribution, we also consider the influence of locality, i.e., if the location swaps are restricted to swaps of neighboring agents. We give improved almost tight bounds on the Price of Anarchy for arbitrary underlying graphs and we present (almost) tight bounds for regular graphs, paths and cycles. Moreover, we give almost tight bounds for grids, which are commonly used in empirical studies. For grids we also show that locality has a severe impact on the game dynamics.
Funder
Universität Potsdam
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Reference42 articles.
1. Agarwal, A., Elkind, E., Gan, J., Igarashi, A., Suksompong, W., & Voudouris, A. A. (2021). Schelling games on graphs. Artificial Intelligence, 301, 103576. 2. Aits, D., Carver, A., & Turrini, P. (2019). Group segregation in social networks. In: AAMAS’19, pp. 1524–1532. 3. Anshelevich, E., Dasgupta, A., Kleinberg, J., Tardos, E., Wexler, T., & Roughgarden, T. (2008). The price of stability for network design with fair cost allocation. SIAM Journal on Computing, 38(4), 1602–1923. 4. Aziz, H., Brandl, F., Brandt, F., Harrenstein, P., Olsen, M., & Peters, D. (2019). Fractional hedonic games. ACM Transactions on Economics and Computation, 7(2), 1–29. 5. Barmpalias, G., Elwes, R., & Lewis-Pye, A. (2014). Digital morphogenesis via schelling segregation. In: FOCS’14, pp. 156–165.
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|