The policy sharing between 40 runs of MC-EMMA with RL-CSP is organised via the common policy vector . All runs start simultaneously but choose the initial structure independently. Each run follows its own trajectory (sequence of structures and actions) and does not consider the trajectories of other runs. Given the current structure, a run selects an action according to the shared policy , observes a new structure and updates according to the reward obtained. When the run finds the global minimum, it stops while other working runs continue following their own trajectories in which they did not find the global minimum yet. Fig. demonstrates the shared policy learned by 40 runs of MC-EMMA with RL-CSP.