Theory of Computing
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Title : Nash Equilibria in Perturbation-Stable Games
Authors : Maria-Florina Balcan and Mark Braverman
Volume : 13
Number : 13
Pages : 1-31
URL : https://theoryofcomputing.org/articles/v013a013
Abstract
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Motivated by the fact that in many game-theoretic settings, the game
analyzed is only an approximation to the game being played, in this
work we analyze equilibrium computation for the broad and natural
class of bimatrix games that are stable under perturbations. We
specifically focus on games with the property that small changes in
the payoff matrices do not cause the Nash equilibria of the game to
fluctuate wildly. For such games we show how one can compute
approximate Nash equilibria more efficiently than the general result
of Lipton et al. (EC'03), by an amount that depends on the degree of
stability of the game and that reduces to their bound in the worst
case. Additionally, we show that for stable games, the approximate
equilibria found will be close in variation distance to true
equilibria, and moreover this holds even if we are given as input only
a perturbation of the actual underlying stable game.
For uniformly stable games, where the equilibria fluctuate at most
quasi-linearly in the extent of the perturbation, we get a
particularly dramatic improvement. Here, we achieve a fully quasi-
polynomial-time approximation scheme, that is, we can find
$1/poly(n)$-approximate equilibria in quasi-polynomial time. This is
in marked contrast to the general class of bimatrix games for which
finding such approximate equilibria is PPAD-hard. In particular, under
the (widely believed) assumption that PPAD is not contained in quasi-
polynomial time, our results imply that such uniformly stable games
are inherently easier for computation of approximate equilibria than
general bimatrix games.