یک کلاس از تداخل ناشی از بازی: تعادل نش مجانبی و راه حل های تعاونی پارامتری شده

We consider a multi-agent system with linear stochastic individual dynamics, and individual linear quadratic ergodic cost functions. The agents partially observe their own states. Their cost functions and initial statistics are a priori independent but they are coupled through an interference term (the mean of all agent states), entering each of their individual measurement equations. While in general for a finite number of agents, the resulting optimal control law may be a non linear function of the available observations, we establish that for certain classes of cost and dynamic parameters, optimal separated control laws obtained by ignoring the interference coupling, are asymptotically optimal when the number of agents goes to infinity, thus forming for finite NN, an ϵϵ-Nash equilibrium. More generally though, optimal separated control laws may not be asymptotically optimal, and can in fact result in unstable overall behavior. Thus we consider a class of parameterized decentralized control laws whereby the separated Kalman gain is treated as the arbitrary gain of a Luenberger like observer. System stability regions are characterized and the nature of optimal cooperative control policies within the considered class is explored. Numerical results and an application example for wireless communications are reported.