Volodymyr Mnih and his colleagues at DeepMind formalized the Asynchronous Advantage Actor-Critic (A3C) algorithm, allowing multiple agent threads to interact with parallel environments simultaneously, heavily stabilizing reinforcement learning policy optimization.
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