Computation of the Closed-Loop Stackelberg Solution Using the Genetic Algorithm

摘要

This paper deals with the computation of the closed-loop dynamic Stackelberg equilibrium solution in two-player nonzero-sum dynamic games using the genetic algorithm. When the leader has access to closed-loop state information, which provides him(indirectly) with on-line information on the past actions of the follower, derivation of the Stackelberg solution is known to be a challenging one. We address here the question of whether in this context genetic algorithm techniques or their appropriately modified versions can be used as computational tools. Following demonstrations using analytic derivations in general linear quadratic games, the paper applies the tool to a nonlinear dynamic taxation problem.