There are 1 repository under ppo-pytorch topic.
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
PyTorch implementation of some reinforcement learning algorithms: A2C, PPO, Behavioral Cloning from Observation (BCO), GAIL.
Implementation of PPO Lagrangian in PyTorch
Multi agent PPO implementation in Pytorch for Unity ML Agents environments.
PyTorch implementation of GAIL and PPO reinforcement learning algorithms
DRL-Base-EMS for HEVs
GAIL learning to imitate PPO playing CartPole.
This is the Tic-Tac-Toe game made with Python using the PyGame library and the Gym library to implement the AI with Reinforcement Learning
Minimum viable reinforcement learning algorithms for your educational convenience.
Reinforcement learning (PPO) plays Mario.
implementation of reinforcement learning algorithm that is easy to read and understand
Positioning a building mass on topography while minimizing the required cut and fill excavation volume using actor critic methods.
Repository with all source files relating to the 6CCE3EEP Final Year Project titled "Self Parking with Reinforcement Learning." The project was implemented using Python, and used PyGame, OpenAI Gym, and the Stable Baselines-3 libraries in order to implement a Proximal Policy Optimisation (PPO) algorithm.
An adaption of the Flatland environment for TorchRL.
Worst-case MSE Minimization for RIS-assisted mmWave MU-MISO Systems with Hardware Impairments and CSI Imperfection
Proximal Policy Optimization method in Pytorch
Agent trained to play battleship using reinforcement learning (PPO) and openAI gym
Deep RL implementations. DQN, SAC, DDPG, TD3, PPO and VPG implemented in pytorch. Tested Env: LunarLander-v2 and Pendulum-v0.
A deep reinforcement learning Bot for https://kana.byha.top:444/
PyTorch application of reinforcement learning Advanced Policy Gradient algorithms in OpenAI BipedalWalker- PPO
HAMMER: Multi-Level Coordination of Reinforcement Learning Agents via Learned Messaging (Paper: https://ala2021.vub.ac.be/papers/ALA2021_paper_35.pdf)
self driving car using Torcs-1.3.7 simulator with server-patch
Deep RL Agent using Proximal Policy Optimization for solving the Pong game.
PyTorch application of reinforcement learning DDPG and PPO algorithms in Unity 3D-Ball
The Improved version of PyLife (now with AI)
An implementation from the state-of-the-art family of reinforcement learning algorithms Proximal Policy Optimization using normalized Generalized Advantage Estimation and optional batch mode training. The loss function incorporates an entropy bonus.
This is a Deep-Q Learning [Stable Baseline] based AI Mario Game where the Model Incrementally Learns and Improves to Play the Game.
Deep Reinforcement Learning algorithms to play Connect4 using a combination of Supervised Learning and Reinforcement Learning
Muno server for bandwidth estimation in video conferencing