Multi-threading parallel reinforcement learning

With respect to the problem of the slow convergence of the traditional reinforcement learning algorithm in practical applications, we propose a novel multi-threading parallel reinforcement learning algorithm - MPRL. MPRL is mainly composed of two parts. One is the FCM-based reinforcement learning multi-threading partitioning method, which transforms the multi-threading partitioning problem into a clustering partition problem to obtain the …