8,800 research outputs found
Query Complexity of Approximate Nash Equilibria
We study the query complexity of approximate notions of Nash equilibrium in
games with a large number of players . Our main result states that for
-player binary-action games and for constant , the query
complexity of an -well-supported Nash equilibrium is exponential
in . One of the consequences of this result is an exponential lower bound on
the rate of convergence of adaptive dynamics to approxiamte Nash equilibrium
A Parameterisation of Algorithms for Distributed Constraint Optimisation via Potential Games
This paper introduces a parameterisation of learning algorithms for distributed constraint optimisation problems (DCOPs). This parameterisation encompasses many algorithms developed in both the computer science and game theory literatures. It is built on our insight that when formulated as noncooperative games, DCOPs form a subset of the class of potential games. This result allows us to prove convergence properties of algorithms developed in the computer science literature using game theoretic methods. Furthermore, our parameterisation can assist system designers by making the pros and cons of, and the synergies between, the various DCOP algorithm components clear
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