Approximating solutions for nonlinear dynamic tracking games

This paper presents the OPTGAME algorithm developed to iteratively approximate equilibrium solutions of ‘tracking games’, i.e. discrete-time nonzero-sum dynamic games with a finite number of players who face quadratic objective functions. Such a tracking game describes the behavior of decision makers who act upon a nonlinear discrete-time dynamical system, and who aim at minimizing the deviations from individually desirable paths of multiple states over a joint finite planning horizon. Among the noncooperative solution concepts, the OPTGAME algorithm approximates feedback Nash and Stackelberg equilibrium solutions, and the open-loop Nash solution, and the cooperative Pareto-optimal solution