This repository contains an implementation of the RL Algorithm Proximal Policy Optimization. The implementation is based on the paper Proximal Policy Optimization Algorithms by Schulman et al. and is ...

Abstract: In recent years, reinforcement learning (RL) has emerged as a solution ... Therefore, we propose an improved proximal policy optimization algorithm for sequential security-constrained ...

Policy gradient methods are a class of RL algorithms that optimize the agent's policy, which is a function that maps states to actions. Proximal policy optimization (PPO) is a popular and ...

The system simulates a building with multiple elevators and floors, and uses the PPO (Proximal Policy Optimization) algorithm from Stable Baselines3 to optimize elevator dispatching.

However, there remains a considerable gap between such theoretically analyzed algorithms and the ones used in practice. Inspired by this, we propose an efficient RL algorithm, called {\em mirror ...