A Distributed Algorithm for Optimising over Pure Strategy Nash Equilibria
A Distributed Algorithm for Optimising over Pure Strategy Nash Equilibria
We develop an efficient algorithm for computing pure strategy Nash equilibria that satisfy various criteria (such as the utilitarian or Nash--Bernoulli social welfare functions) in games with sparse interaction structure. Our algorithm, called Valued Nash Propagation (VNP), integrates the optimisation problem of maximising a criterion with the constraint satisfaction problem of finding a game's equilibria to construct a criterion that defines a c-semiring. Given a suitably compact game structure, this criterion can be efficiently optimised using message-passing. To this end, we first show that VNP is complete in games whose interaction structure forms a hypertree. Then, we go on to provide theoretic and empirical results justifying its use on games with arbitrary structure; in particular, we show that it computes the optimum >82% of the time and otherwise selects an equilibrium that is always within 2% of the optimum on average.
Game theory, distributed optimisation
749-755
Chapman, Archie
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Farinelli, Alessandro
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Munoz De Cote Flores Luna, Jose Enrique
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Rogers, Alex
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Jennings, Nicholas R.
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July 2010
Chapman, Archie
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Farinelli, Alessandro
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Munoz De Cote Flores Luna, Jose Enrique
afb4bdd8-8511-4961-a639-15521220a213
Rogers, Alex
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Jennings, Nicholas R.
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Chapman, Archie, Farinelli, Alessandro, Munoz De Cote Flores Luna, Jose Enrique, Rogers, Alex and Jennings, Nicholas R.
(2010)
A Distributed Algorithm for Optimising over Pure Strategy Nash Equilibria.
Twenty-Fourth AAAI Conference on Artificial Intelligence, Atlanta, USA, Georgia.
11 - 15 Jul 2010.
.
Record type:
Conference or Workshop Item
(Other)
Abstract
We develop an efficient algorithm for computing pure strategy Nash equilibria that satisfy various criteria (such as the utilitarian or Nash--Bernoulli social welfare functions) in games with sparse interaction structure. Our algorithm, called Valued Nash Propagation (VNP), integrates the optimisation problem of maximising a criterion with the constraint satisfaction problem of finding a game's equilibria to construct a criterion that defines a c-semiring. Given a suitably compact game structure, this criterion can be efficiently optimised using message-passing. To this end, we first show that VNP is complete in games whose interaction structure forms a hypertree. Then, we go on to provide theoretic and empirical results justifying its use on games with arbitrary structure; in particular, we show that it computes the optimum >82% of the time and otherwise selects an equilibrium that is always within 2% of the optimum on average.
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cfmrj_AAAI_2010.pdf
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Published date: July 2010
Additional Information:
Event Dates: 11 - 15 July, 2010
Venue - Dates:
Twenty-Fourth AAAI Conference on Artificial Intelligence, Atlanta, USA, Georgia, 2010-07-11 - 2010-07-15
Keywords:
Game theory, distributed optimisation
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 270818
URI: http://eprints.soton.ac.uk/id/eprint/270818
PURE UUID: 5bd31b00-e026-4172-8c80-451277d328fe
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Date deposited: 09 Apr 2010 14:15
Last modified: 14 Mar 2024 09:17
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Contributors
Author:
Archie Chapman
Author:
Alessandro Farinelli
Author:
Jose Enrique Munoz De Cote Flores Luna
Author:
Alex Rogers
Author:
Nicholas R. Jennings
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