Policy Gradient Theorem Explained: A Hands-On Introduction

Reinforcement learning (RL) utilizes policy gradient algorithms to directly optimize an agent's policy. These algorithms estimate the gradient of the expected reward relative to the policy's parameters.

This guide provides a practical explanation of the policy gradient theorem, its derivation, and a PyTorch implementation of the policy gradient algorithm.

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