Actualités

IEEE1 a
Improved Proximal Policy Optimization Algorithm for Sequential Security-Constrained Optimal Power Flow Based on Expert Knowledge and Safety Layer
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 ...
GitHub7 a
Proximal_Policy_Optimization_Algorithms.md
As far as I understand, Proximal Policy Optimization itself isn't new ... I need to collect a set of all the policy gradient algorithms I need to know, DDPG, TNPG, TRPO, PPO, and obviously implement ...
GitHub2 a
VerleysenNiels/PPO-pytorch-gym
The PPO algorithm involves two main steps ... (2017): "Proximal Policy Optimization Algorithms". For more information on using reinforcement learning in OpenAI Gym, see the official documentation: ...
marktechpost1 a
REBEL: A Reinforcement Learning RL Algorithm that Reduces the Problem of RL to Solving a Sequence of Relative Reward Regression Problems on Iteratively Collected Datasets
Initially designed for continuous control tasks, Proximal Policy ... Are there simpler algorithms that scale to modern RL applications? Policy Gradient (PG) methods, renowned for their direct, ...
Microsoft3 a
Mirror Descent Policy Optimization
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 ...