On finite-horizon approximation of an infinite-horizon feedback Nash equilibrium in discrete-time LQ games
The episode discusses a paper approximating infinite-horizon feedback Nash equilibria in discrete-time LQ games by using finite-horizon approximations. The hosts explain how players can solve smaller, simpler games iteratively instead of one large system. They conclude that this method is computationally tractable and provides an explicit bound on the performance error, allowing engineers to tune the prediction horizon for real-world applications.