DocumentCode
2318175
Title
Selection of efficient pure strategies in allocation games
Author
Coucheney, Pierre ; Touati, Corinne ; Gaujal, Bruno
Author_Institution
INRIA Rhone-Alpes, Grenoble, France
fYear
2009
fDate
13-15 May 2009
Firstpage
658
Lastpage
666
Abstract
In this work we consider allocation games and we investigate the following question: under what conditions does the replicator dynamics select a pure strategy? By definition, an allocation game is a game such that the payoff of a player when she takes an action only depends on the set of players who also take the same action. Such a game can be seen as a set of users who share a set of resources, a choice being an allocation to a resource. A companion game (with modified utilities) is introduced. From the payoffs of an allocation game, we define the repercussion utilities: for each player, her repercussion utility is her payoff minus the decrease in marginal payoff that her presence causes to all other players. The corresponding allocation game with repercussion utilities is the game whose payoffs are the repercussion utilities. A simple characterization of those games is given. In such games, if the players select their strategy according to a stochastic approximation of the replicator dynamics, we show that it converges to a Nash equilibrium of the game that is a locally optimal for the initial game. The proof is based on the construction of a potential function for the game. Furthermore, a spectral study of the dynamics shows that no mixed equilibrium is stable, so that the strategies of all players converge to a set of Nash equilibria. Then, martingale argument prove the convergence of the stochastic approximation to a pure point. A discussion of the global/local optimality of the limit points is also included.
Keywords
approximation theory; convergence of numerical methods; stochastic games; Nash equilibrium convergence; allocation game; companion game; efficient pure strategy; players payoff; potential function; repercussion utility; replicator dynamics; resource allocation; stochastic approximation; Biological system modeling; Computational biology; Convergence; Evolution (biology); Game theory; Laboratories; Nash equilibrium; Resource management; Routing; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Game Theory for Networks, 2009. GameNets '09. International Conference on
Conference_Location
Istanbul
Print_ISBN
978-1-4244-4176-1
Electronic_ISBN
978-1-4244-4177-8
Type
conf
DOI
10.1109/GAMENETS.2009.5137457
Filename
5137457
Link To Document