Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
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Updated
Mar 29, 2023 - Python
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
IEEE WCNC 2023: Deep Reinforcement Learning for Secrecy Energy-Efficient UAV Communication with Reconfigurable Intelligent Surfaces
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
A codebase for continuous action spaces Reinforcement Learning algorithms
Implementation of Reinforcement Learning Based Autonmous Control of a TurtleBot2 as a substitute for a Formula SAE Car
A PyTorch implementation of the DRL algorithm TD3
A Decentralized, Fully Autonomous Drone Delivery System for Reliable, Efficient Transport of Goods
Implementation of TD3 agent in PyTorch.
A novel and efficient methodology that enables the robot to maneuver safely through dense crowds in more ‘human-like’ patterns.
Twin Delayed DDPG
Aligning an optical interferometer with beam divergence control and continuous action space.
Tests SOTA algorithms using pendulum as baseline environment
tabular and deep rl algorithms
Project for Artificial Intelligence course at University of Ljubljana, Faculty of Computer and Information science.
The pytorch implementation of td3
Develop and implement reinforcement learning for real-world navigation in DuckieTown, optimizing performance and resilience for reliable autonomous movement, backed by interpretable decision-making tools.
Deep Reinforcement Learning for mobile robot navigation in ROS2 Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.
TD3 and PPO implementation -- Final project for the course ELEC-E8125 Reinforcement Learning at Aalto University
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