A Torch Based RL Framework for Rapid Prototyping of Research Papers
-
Updated
Jul 29, 2024 - Python
A Torch Based RL Framework for Rapid Prototyping of Research Papers
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)
An intelligent PACMAN agent built using Reinforcement learning.
This repository implements the use of AI for robot tasks.
Modularized Implementation of Deep RL Algorithms in PyTorch
Implementation of the Double Deep Q-Learning algorithm with a prioritized experience replay memory to train an agent to play the minichess variante Gardner Chess
Third homework for the Reinforcement Learning course
Actor Prioritized Experience Replay
gym environnement to simulate the energetic behaviour of a real estate
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
Implementation code when learning deep reinforcement learning
RLCodebase: PyTorch Codebase For Deep Reinforcement Learning Algorithms
Prioritized Experience Replay implementation with proportional prioritization
Deep Reinforcement Learning: Value-Based methods. An implementation of DQN, DDQN, Dueling Architectures, DQV, DQV-Max on the PyTorch Lightning framework.
Deep RL for Pixel-based Environments
Implementation of RL Algorithms with PyTorch.
An implementation of Deep Q-Learning Network for solving a Unity environment that can navigate and collect bananas in a large, square world.
Pytorch implementation of distributed deep reinforcement learning
A very detailed project of Chrome Dinosaur in Deep RL for beginners
Add a description, image, and links to the prioritized-experience-replay topic page so that developers can more easily learn about it.
To associate your repository with the prioritized-experience-replay topic, visit your repo's landing page and select "manage topics."