Selfish routing with incomplete information

Abstract

In his seminal work Harsanyi [13] introduced an elegant approach to study non-cooperative games with incomplete information where the players are uncertain about some parameters. To model such games he introduced the Harsanyi transformation, which converts a game with incomplete information to a strategic game where players may have different types. In the resulting Bayesian game players' uncertainty about each others types is described by a probability distribution over all possible type profiles.In this work, we introduce a particular selfish routing game with incomplete information that we call Bayesian routing game. Here, n selfish users wish to assign their traffic to one of m links. Users do not know each others traffic. Following Harsanyi's approach, we introduce for each user a set of possible types.This paper presents a comprehensive collection of results for the Bayesian routing game.We prove, with help of a potential function, that every Bayesian routing game possesses a pure Bayesian Nash equilibrium. For the model of identical links and independent type distribution we give a polynomial time algorithm to compute a pure Bayesian Nash equilibrium.We study structural properties of fully mixed Bayesian Nash equilibria for the model of identical links and show that they maximize individual cost. In general there exists more than one fully mixed Bayesian Nash equilibrium. We characterize the class of fully mixed Bayesian Nash equilibria in the case of independent type distribution.We conclude with results on coordination ratio for the model of identical links for three social cost measures, that is, social cost as expected maximum congestion, sum of individual costs and maximum individual cost. For the latter two we are able to give (asymptotic) tight bounds using our results on fully mixed Bayesian Nash equilibria.To the best of our knowledge this is the first time that mixed Bayesian Nash equilibria have been studied in conjunction with social cost.

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