We propose an approach to saddle point optimization relying only on oracles that solve minimization problems approximately. analyze its convergence property a strongly convex--concave problem and show linear toward the global min--max point. Based analysis, we develop heuristic adapt learning rate. An implementation of developed using (1+1)-CMA-ES as oracle, namely Adversarial-CMA-ES, is shown ...