Genetic algorithm for closed-loop equilibrium of high-order linear-quadratic dynamic games

Abstract

In this paper, we implement an adaptive search algorithm, genetic algorithm to derive closed-loop Nash equilibria for linear-quadratic dynamic games. The computation of these equilibria is quite difficult to deal with analytically and numerically. Our strategy is to search over all time-invariant strategies depending only on the current value of the state. Also provided are some evidences which show the success of the algorithm.