Proximal Policy Optimization (PPO)Algorithm in Machine Learning

[alo7lika]

Closes: #1434

Description

PPO is a widely used reinforcement learning algorithm that improves training stability and performance by balancing exploration and exploitation through its innovative policy update mechanism. This algorithm is particularly effective in various applications, including robotics, game-playing, and natural language processing.

Key Features of PPO:

• Clipped Objective Function: Ensures stable updates by limiting how much the policy can change in one step.
• On-Policy Learning: Adapts the policy based on the latest data collected from the environment.
• Generalized Advantage Estimation (GAE): Reduces variance in policy gradient estimates, leading to more efficient learning.

Issue_Reference: #1434

[alo7lika]

@pankaj-bind the task has been completed. Kindly Review it