Logo image
The Impact of Social Ignorance on Weighted Congestion Games
Conference proceeding   Peer reviewed

The Impact of Social Ignorance on Weighted Congestion Games

Dimitris Fotakis, Vasilis Gkatzelis, Alexis C. Kaporis and Paul G. Spirakis
INTERNET AND NETWORK ECONOMICS, PROCEEDINGS, v 5929, pp 316-327
01 Jan 2009
url
http://doi.org/10.1007/978-3-642-10841-9_29View
Open

Abstract

Computer Science Computer Science, Theory & Methods Science & Technology Technology
We consider weighted linear congestion games, and investigate how social ignorance, namely lack of information about the presence of some players, affects the inefficiency of pure Nash equilibria (PNE) and the convergence rate of the epsilon-Nash dynamics. To this end, we adopt the model of graphical linear congestion games with weighted players, where the individual cost and the strategy selection of each player only depends on his neighboring players in the social graph. We show that such games admit a potential function, and thus a PNE. Our main result is that the impact of social ignorance on the Price of Anarchy (PoA) and the Price of Stability (PoS) is naturally quantified by the independence number alpha(G) of the social graph C. In particular, we show that the NA grows roughly as alpha(G)(alpha(G) + 2), which is essentially tight as long as alpha(G) does not exceed half the number of players, and that the PoS lies between alpha(G) and 2 alpha(G). Moreover, we show that the epsilon-Nash dynamics reaches an alpha(G)(alpha(G)+2)-approximate configuration in polynomial time that does not directly depend on the social graph. For unweighted graphical linear games with symmetric strategies, we show that the epsilon-Nash dynamics reaches an epsilon-approximate PNE in polynomial time that exceeds the corresponding time for symmetric linear games by a factor at most as large as the number of players.

Metrics

9 Record Views
10 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#10 Reduced Inequalities

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Theory & Methods
Logo image