Mixed cooperative-competitive control scenarios such as human-machine\ninteraction with individual goals of the interacting partners are very\nchallenging for reinforcement learning agents. In order to contribute towards\nintuitive human-machine collaboration, we focus on problems in the continuous\nstate and control domain where no explicit communication is considered and the\nagents do not know the others' goals or control laws but only sense their\ncontrol inputs retrospectively. Our proposed framework combines…