No abstract

In this paper, we consider the problem of learning a correlated equilibrium of a finite non-cooperative game and show a new adaptive heuristic, called Correlated Perturbed Regret Minimization (CPRM) for this purpose. CPRM combines regret minimization to approach the set of correlated equilibria and a simple device suggesting actions to the players to further stabilize the dynamic. Numerical experiments support the hypothesis of the pointwise convergence of the empirical distribution over action profiles to an approximate correlated equilibrium with all players following the devices' suggestions. Additional simulation results suggest that CPRM is adaptive to changes in the game such as departures or arrivals of players.

In this paper, centralized and distributed multiregion perimeter flow control approaches are proposed for congestion avoidance in urban networks. First, multi-region network dynamics are modeled with Macroscopic Fundamental Diagrams (MFDs) and necessary stability conditions are derived using Lyapunov stability theory for a centralized perimeter controller. Later, an optimization problem is formulated, solved and the desired optimal states are reached by means of an algorithm based on Model Predictive Control (MPC). Finally, the paper combines the centralized controller for perimeter control as a first layer controller and a distributed controller managing the inter-transfers between regions, thus optimizing the overall state of the network. Simulations show that the distributed control scheme leads to good results maximizing the output of the traffic network, similar to the MPC controller.