Computational Economics

, Volume 45, Issue 3, pp 407–433

Approximating Solutions for Nonlinear Dynamic Tracking Games


DOI: 10.1007/s10614-014-9420-4

Cite this article as:
Behrens, D.A. & Neck, R. Comput Econ (2015) 45: 407. doi:10.1007/s10614-014-9420-4


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.


Dynamic game theory Algorithm Noncooperative game Cooperative game Tracking problem Nash equilibrium Markov-perfect equilibrium Stackelberg equilibrium Pareto optimum 

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Controlling and Strategic ManagementAlpen-Adria Universität KlagenfurtKlagenfurt/WörtherseeAustria
  2. 2.Lakeside Labs GmbHKlagenfurt/WörtherseeAustria
  3. 3.Department of Mathematical Methods in EconomicsVienna University of TechnologyViennaAustria
  4. 4.Department of EconomicsAlpen-Adria Universität KlagenfurtKlagenfurt/WörtherseeAustria

Personalised recommendations