A distributed routing control algorithm for dynamic networks has recently been presented in the literature. The networks were modeled using time evolution of density at network edges and the routing control algorithm allowed edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We borrow the idea and rearrange the density model to recast the problem within the framework of mean-field games. The contribution of this paper is three-fold. First, we provide a mean-field game formulation of the problem at hand. Second, we illustrate an extended state space solution approach. Third, we study the stochastic case where the density evolution is driven by a Brownian motion.

Bauso, D., Zhang, X., Papachristodulou, A. (2014). Density Flow over Networks: A Mean-field Game Theoretic Approach. In Proc of IEEE Conference on Decision and Control (pp.3469-3474) [10.1109/CDC.2014.7039927].

Density Flow over Networks: A Mean-field Game Theoretic Approach

BAUSO, Dario;
2014-01-01

Abstract

A distributed routing control algorithm for dynamic networks has recently been presented in the literature. The networks were modeled using time evolution of density at network edges and the routing control algorithm allowed edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We borrow the idea and rearrange the density model to recast the problem within the framework of mean-field games. The contribution of this paper is three-fold. First, we provide a mean-field game formulation of the problem at hand. Second, we illustrate an extended state space solution approach. Third, we study the stochastic case where the density evolution is driven by a Brownian motion.
Settore ING-INF/04 - Automatica
Settore MAT/09 - Ricerca Operativa
2014
IEEE Conference on Decision and Control
Los Angeles
Dicembre 2014
2014
6
Bauso, D., Zhang, X., Papachristodulou, A. (2014). Density Flow over Networks: A Mean-field Game Theoretic Approach. In Proc of IEEE Conference on Decision and Control (pp.3469-3474) [10.1109/CDC.2014.7039927].
Proceedings (atti dei congressi)
Bauso, D; Zhang, X; Papachristodulou, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/169144
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