Conference proceeding
Structural Stability of a Family of Group Formation Games
2021 60th IEEE Conference on Decision and Control (CDC), Vol.2021-, pp.3080-3085
01/01/2021
DOI: 10.1109/CDC45484.2021.9683571
Abstract
We introduce and study a group formation game in which individuals/agents, driven by self-interest, team up in disjoint groups so as to be in groups of high collective strength. This strength could be group identity, reputation, or protection, and is equally shared by all group members. The group's access to resources, obtained from its members, is traded off against the geographic dispersion of the group: spread-out groups are more costly to maintain. We seek to understand the stability and structure of such partitions. We define two types of equilibria:1)Acceptance Equilibria (AE), in which no agent will unilaterally change group affiliation, either because the agent cannot increase her utility by switching, or because the intended receiving group is unwilling to accept her (i.e., the utility of existing members would decrease if she joined); and2)Strong Acceptance Equilibria (SAE), in which no subset of any group will change group affiliations (move together) for the same reasons given above.We show that under natural assumptions on the group utility functions, both an AE and SAE always exist, and that any sequence of improving deviations by agents (resp., subsets of agents in the same group) converges to an AE (resp., SAE). We then characterize the properties of the AEs. We show that an "encroachment" relationship - which groups have members in the territory of other groups - always gives rise to a directed acyclic graph (DAG); conversely, given any DAG, we can construct a game with suitable conditions on the utility function that has an AE with the encroachment structure specified by the given graph.
Details
- Title: Subtitle
- Structural Stability of a Family of Group Formation Games
- Creators
- Chenlan Wang - University of Michigan–Ann ArborMehrdad Moharrami - University of Illinois Urbana-ChampaignKun Jin - University of Michigan–Ann ArborDavid Kempe - University of Southern CaliforniaP. Jeffrey Brantingham - University of California, Los AngelesMingyan Liu - University of Michigan–Ann Arbor
- Resource Type
- Conference proceeding
- Publication Details
- 2021 60th IEEE Conference on Decision and Control (CDC), Vol.2021-, pp.3080-3085
- Publisher
- IEEE
- DOI
- 10.1109/CDC45484.2021.9683571
- ISSN
- 0743-1546
- eISSN
- 2576-2370
- Language
- English
- Date published
- 01/01/2021
- Academic Unit
- Computer Science
- Record Identifier
- 9984446451702771
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