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Machine Learning Actor-Critic Methods
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What is the main goal of an actor-critic method?
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A
To find the optimal policy for a given environment
💡 Explanation:
Actor-critic methods are a class of reinforcement learning algorithms that aim to find the optimal policy for a given environment by combining an actor network, which learns to select actions, and a critic network, which learns to evaluate the value of states.