Year: 2016
Type: preprint
Abstract: We study the problem of finding approximate Nash equilibria that satisfy certain conditions, such as providing good social welfare. In particular, we study the problem $ε$-NE $δ$-SW: find an $ε$-approximate Nash equilibrium ($ε$-NE) that is within $δ$ of the best social welfare achievable by an $ε$-NE. Our main result is that, if the exponential-time hypothesis (ETH) is true, then solving $\left(\frac{1}{8} - \mathrm{O}(δ)\right)$-NE $\mathrm{O}(δ)$-SW for an $n\times n$ bimatrix game requires $n^{\mathrm{\widetilde Ω}(\log n)}$ time. Building on this result, we show similar conditional running time lower bounds on a number of decision problems for approximate Nash equilibria that do not involve social welfare, including maximizing or minimizing a certain player's payoff, or finding approximate equilibria contained in a given pair of supports. We show quasi-polynomial lower bounds for these problems assuming that ETH holds, where these lower bounds apply to $ε$-Nash equilibria for all $ε< \frac{1}{8}$. The hardness of these other decision problems has so far only been studied in the context of exact equilibria.
Source: arXiv (Cornell University)
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2950879023