Deep Reinforcement Learning with Python: RLHF for Chatbots and Large Language Models

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2024

N. SanghiDeep Reinforcement Learning with Pythonhttps://doi.org/10.1007/979-8-8688-0273-7_8

8. Policy Gradient Algorithms

Nimish Sanghi¹  

(1)

Bangalore, India

 

Up to now, the book has focused on model-based and model-free methods. All the algorithms using these methods estimate the state or state-action values for a given current policy as the first step. In the second step, these estimated values are used to find a better policy by choosing the best action in a given state. These two steps are carried out in a loop until no further improvement in values is observed. In this chapter, you look at a different approach for learning optimal policies, by directly ...