Internet of Things (IoT) Systems
Policy gradient is a type of reinforcement learning algorithm that optimizes the policy directly, using gradients to improve the likelihood of actions that lead to higher rewards. This approach is particularly useful in environments where the action space is continuous or high-dimensional, allowing for more nuanced decision-making. By adjusting the parameters of the policy based on feedback from the environment, policy gradient methods can efficiently learn optimal strategies for complex tasks.
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