Policy Gradient Methods

Policy Gradient Methods are a class of algorithms in reinforcement learning that optimize the policy directly rather than through value functions. These methods are crucial for training agents in complex environments where traditional methods may struggle. Understanding and implementing these techniques can significantly enhance the performance of AI systems in various applications.