#算法刷题#PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
IEEE WCNC 2023: Deep Reinforcement Learning for Secrecy Energy-Efficient UAV Communication with Reconfigurable Intelligent Surfaces
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
3D game prototype using GLKit and ARC under iOS 5
Solve BipedalWalkerHardcore-v2 with TD3
Twin Delayed DDPG (TD3) PyTorch solution for Roboschool and Box2d environment
The implementation of LSTM-TD3.
Implementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
#计算机科学#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)
DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)
#计算机科学#Use Multi-agent Twin Delayed Deep Deterministic Policy Gradient(TD3) algorithm to find reasonable paths for ships
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
#算法刷题#Basic reinforcement learning algorithms. Including:DQN,Double DQN, Dueling DQN, SARSA, REINFORCE, baseline-REINFORCE, Actor-Critic,DDPG,DDPG for discrete action space, A2C, A3C, TD3, SAC, TRPO
#计算机科学#Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal...
#计算机科学#Deep Reinforcement Learning for mobile robot navigation in ROS2 Gazebo simulator. Using DRL (SAC, TD3) neural networks, a robot learns to navigate to a random goal point in a simulated environment whi...