ddpg-pytorch

Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

Deep Reinforcement Learning for mobile robot navigation in IR-SIM simulation. Using DRL (SAC, TD3, PPO, DDPG) neural networks, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.

A Modular Library for Off-Policy Reinforcement Learning with a focus on SafeRL and distributed computing

强化学习算法库，包含了目前主流的强化学习算法(Value based and Policy based)的代码，代码都经过调试并可以运行

A Torch Based RL Framework for Rapid Prototyping of Research Papers

Simulation based Soft Continuum Robot Control via Reinforcement Learning

The simulation of paper: Joint Cooperation Clustering and Content Caching in Cell-Free Massive MIMO Networks

Implement reinforcement learning algorithms in Pytorch

Multi-agent reinforcement learning framework

An implementation of DDPG using PyTorch for algorithmic trading on Chinese SH50 stock market.

Reinforcement Learning Tutorials & other bedtime stories in PyTorch

La combinación más inteligente de Deep Q-Learning, Políticas de Gradiente, Actor-Crítico y DDPG utilizando PyTorch

PyTorch implementation of the paper Overcoming Exploration in Reinforcement Learning with Demonstrations in surgical robot manipulation tasks.

A simple baseline for mountain-car @ gym

Common deep reinforcement learning algorithms implemented using PyTorch, including DQN、DDPG、DDQN、PPO、MADDPG.

PyTorch application of reinforcement learning algorithm in OpenAI LunarLander - DDPG

Twin Delayed Deep Deterministic Policy Gradient Algorithm On PybulletAnt agent.

Deep Deterministic Policy Gradients in Pytorch with Simulation in PyBullet

Performance evaluation of several DRL algorithms in a discrete action-space for resource allocation in Open RAN

This repository contains an implementation of Deep Deterministic Policy Gradient (DDPG), a reinforcement learning algorithm designed for environments with continuous action spaces. It features actor-critic architecture, experience replay, and exploration strategies, and is tested on environments like MountainCarContinuous. More info on Medium blog!