Abstract

We consider structural and algorithmic questions related to the Nash dynamics of weighted congestion games. In weighted congestion games with linear latency functions, the existence of pure Nash equilibria is guaranteed by a potential function argument. Unfortunately, this proof of existence is inefficient and computing pure Nash equilibria in such games is a PLS-hard problem even when all players have unit weights. The situation gets worse when superlinear (e.g., quadratic) latency functions come into play; in this case, the Nash dynamics of the game may contain cycles and pure Nash equilibria may not even exist. Given these obstacles, we consider approximate pure Nash equilibria as alternative solution concepts. A ρ --approximate pure Nash equilibrium is a state of a (weighted congestion) game from which no player has any incentive to deviate in order to improve her cost by a multiplicative factor higher than ρ . Do such equilibria exist for small values of ρ ? And if so, can we compute them efficiently? We provide positive answers to both questions for weighted congestion games with polynomial latency functions by exploiting an “approximation” of such games by a new class of potential games that we call Ψ -games. This allows us to show that these games have d!-approximate pure Nash equilibria, where d is the maximum degree of the latency functions. Our main technical contribution is an efficient algorithm for computing O(1)-approximate pure Nash equilibria when d is a constant. For games with linear latency functions, the approximation guarantee is 3+√5/2 + O γ for arbitrarily small γ > 0; for latency functions with maximum degree d ≥ 2, it is d 2 d + o ( d ). The running time is polynomial in the number of bits in the representation of the game and 1/ γ . As a byproduct of our techniques, we also show the following interesting structural statement for weighted congestion games with polynomial latency functions of maximum degree d ≥ 2: polynomially-long sequences of best-response moves from any initial state to a dO ( d 2)-approximate pure Nash equilibrium exist and can be efficiently identified in such games as long as d is a constant. To the best of our knowledge, these are the first positive algorithmic results for approximate pure Nash equilibria in weighted congestion games. Our techniques significantly extend our recent work on unweighted congestion games through the use of Ψ -games. The concept of approximating nonpotential games by potential ones is interesting in itself and might have further applications.

Highlights

  • In many applications the state of a system depends on the behavior of individual participants that act selfishly in order to minimize their own private cost measured by individual objective functions

  • We study the existence of approximate pure Nash equilibria in weighted congestion games and develop techniques to obtain approximate potential functions that prove the existence of αapproximate pure Nash equilibria and the convergence of α-improvement steps

  • Approximate pure Nash equilibria are only a reasonable concept if the approximation factor is sufficiently close to one. This motivates the main question of this paper: Given a set of cost functions, what is the minimal approximation factor α that one can allow in order to guarantee the existence of an α-approximate pure Nash equilibrium in all weighted congestion games?

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Summary

Introduction

In many applications the state of a system depends on the behavior of individual participants that act selfishly in order to minimize their own private cost measured by individual objective functions. Caragiannis et al [4] show how to compute a 2 + -approximate pure Nash equilibrium in congestion games with affine latencies Subsequent work generalizes this approach to a polynomial algorithm for approximate pure Nash equilibria with constant approximation factor for weighted congestion games with polynomial latency functions [5]. Approximate pure Nash equilibria are only a reasonable concept if the approximation factor is sufficiently close to one This motivates the main question of this paper: Given a set of cost functions, what is the minimal approximation factor α that one can allow in order to guarantee the existence of an α-approximate pure Nash equilibrium in all weighted congestion games?

Our Contribution
Further Related Work
Preliminaries
Existence of an Approximate Potential Function
Bounding the Approximation Factor
Polynomial Cost Functions
Concave Cost Functions
Two-player Games
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