Abstract-The original Braess paradox has been predicted in a context of Wardrop equilibrium in a road traffic context where there is a continuum of (non-atomic) players. It was shown that the performance of all users at equilibrium becomes worse when adding a route. This paradox as well as various variants were also studied in the context of computer networks and telecommunications. We identify a new type of paradox occurring in wireless communications with some unusual properties with respect to previous models in which the paradox has been identified.
International audienceNon-cooperative game theory has gained much interest as a paradigm for decentralized control in communication networks. It allows to get rid of the need for a centralized controller. Decentralizing the decision making may result in situations where agents (decision makers) do not have the same view of the network: the information available to agents vary from one agent to another. The global view of the network state cannot be available to an agent as fast as the information on its local state. Incorporating into the decentralized control paradigm this information asymmetry renders it applicable to a much wider class of situations. In this paper we model the above information asymmetry using the one-step delay sharing information pattern from team theory and generalize it to the context of non-cooperative games. We study its properties and apply it to distributed power control problem
Routing games, as introduced in the pioneering work of Orda, Rom and Shimkin (1993), are very closely related to the traffic assignment problems as already studied by Wardrop and to congestion games, as introduced by Rosenthal. But they exhibit more complex behavior: often the equilibrium is not unique, and computation of equilibria is typically harder. They cannot be transformed in general into an equivalent global optimization problem as is the case with congestion games and in the traffic assignment problem which possess a potential under fairly general conditions. In this paper we study convergence of various learning schemes to an equilibrium in the problem of routing games. We are able to considerably extend previous published results [1] that were restricted to routing into two parallel links. We study evolutionary-based learning algorithms and establish their convergence for general topologies.
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