# Logarithmic Query Complexity for Approximate Nash Computation in Large Games

@article{Goldberg2018LogarithmicQC, title={Logarithmic Query Complexity for Approximate Nash Computation in Large Games}, author={Paul W. Goldberg and Francisco Javier Marmolejo-Coss{\'i}o and Zhiwei Steven Wu}, journal={Theory of Computing Systems}, year={2018}, volume={63}, pages={26-53} }

We investigate the problem of equilibrium computation for “large” n-player games. Large games have a Lipschitz-type property that no single player’s utility is greatly affected by any other individual player’s actions. In this paper, we mostly focus on the case where any change of strategy by a player causes other players’ payoffs to change by at most 1n$\frac {1}{n}$. We study algorithms having query access to the game’s payoff function, aiming to find ε-Nash equilibria. We seek algorithms…

## 3 Citations

Lower Bounds for the Query Complexity of Equilibria in Lipschitz Games

- Economics, MathematicsSAGT
- 2021

This work develops a query-efficient reduction from more general games to Lipschitz games, and provides an exponential lower bound on the deterministic query complexity of finding -approximate correlated equilibria of n-player, m-action, λ-Lipschitzer games for strong values of , motivating the consideration of explicitly randomized algorithms in the above results.

Query complexity of approximate equilibria in anonymous games

- Computer Science, EconomicsJ. Comput. Syst. Sci.
- 2017

Optimally Deceiving a Learning Leader in Stackelberg Games

- EconomicsNeurIPS
- 2020

This paper shows that it is always possible for the follower to efficiently compute (near-)optimal fake payoffs, for various scenarios of learning interaction between the leader and the follower and establishes an interesting connection between the follower's deception and the leader’s maximin utility.

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