where x is the average reward for the self node n, and n p is the number of visits to the self node and the parent node. Default Policy is guaranteed to converge to the optimal solution with a sufficient number of steps even with random selection, but this is not feasible in practice. Machine learning models have been often used in recent years to search efficiently.