Policy iteration is a well-known alternative to algorithms based on value function iterations for the solution of optimal control problems and differential games. In this talk we present a scheme for HJB and Isaacs equations based on a semi-Lagrangian discretization combined with an iterative method in the policy space with accelerated convergence. We highlight the wide applicability of our scheme and its efficient performance in a series of numerical tests.