Performance Bounds for Nash Equilibria in Submodular Utility Systems with User Groups
Yajing Liu, Edwin K. P. Chong, and Ali Pezeshki

TL;DR
This paper analyzes how user grouping and cooperation affect the performance bounds of Nash equilibria in submodular utility systems, providing tighter guarantees and new bounds for social-aware and group Nash equilibria.
Contribution
It introduces new performance bounds for social-aware and group Nash equilibria in grouped utility systems, extending Vetta's results with tighter bounds involving curvature.
Findings
Social-aware Nash equilibria maintain Vetta's bounds.
Group Nash equilibria have a 1/2 performance bound.
Tighter bounds involving group curvature are established.
Abstract
In this paper, we consider variations of the utility system considered by Vetta, in which users are grouped together. Our aim is to establish how grouping and cooperation among users affect performance bounds. We consider two types of grouping. The first type is from \cite{Zhang2014}, where each user belongs to a group of users having social ties with it. For this type of utility system, each user's strategy maximizes its social group utility function, giving rise to the notion of \emph{social-aware Nash equilibrium}. We prove that this social utility system yields to the bounding results of Vetta for non-cooperative system, thus establishing provable performance guarantees for the social-aware Nash equilibrium. For the second type of grouping, the set of users is partitioned into disjoint groups, where the users within a group cooperate to maximize their group utility function,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGame Theory and Applications · Peer-to-Peer Network Technologies · Advanced Bandit Algorithms Research
