Introduction to Proximal Policy Optimization(PPO)
Proximal Policy Optimization (PPO) is a policy gradient-based reinforcement learning algorithm. It is designed to learn an optimal policy for a given environment by iteratively improving upon the current policy. PPO is known for its ability to effectively balance exploration and exploitation, which is a key challenge in reinforcement learning.PPO works by updating the policy using a surrogate objective function that is optimized using stochastic gradient descent.