ASYNCHRONOUS METHOD FOR ACTOR-CRITIC REINFORCEMENT LEARNING
Keywords:
reinforcement learning, actor-critic algorithm, parallel learning, asynchronous gradient descentAbstract
The method of deep reinforcement learning is considered in the work, which implements an asynchronous approach with the use of gradient descent. An actor-critic algorithm based on the proposed method is constructed. Parallel asynchronous algorithm is characterized by a greater stabilizing effect during learning process compared with existing parallel methods. In addition, the proposed approach allows parallelizing the learning process by applying the multi-core properties of modern computers
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