21 results for “topic:drl-pytorch”
Massively Parallel Deep Reinforcement Learning. 🔥
深度强化学习路径规划, SAC-Auto路径规划, Soft Actor-Critic算法, SAC-pytorch,激光雷达Lidar避障,激光雷达仿真模拟,Adaptive-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 high-performance drone deep reinforcement learning platform built upon IsaacGym.
Robot navigation using deep reinforcement learning
SUMO Pytorch Deep Reinforcement Learning Traffic Signal Control
This repo implements Deep Q-Network (DQN) for solving the Frozenlake-v1 environment of the Gymnasium library using Python 3.8 and PyTorch 2.0.1 in both 4x4 and 8x8 map sizes.
This repo implements Deep Q-Network (DQN) for solving the Mountain Car v0 environment (discrete version) of the Gymnasium library using Python 3.8 and PyTorch 2.0.1 with a custom reward function for faster convergence.
记录一些DRL算法实现
This repo contains the Deep Reinforcement Learning algorithm Soft Actor Critic (SAC) implementation in PyTorch
This repo implements Deep Q-Network (DQN) for solving the Cliff Walking v0 environment of the Gymnasium library using Python 3.8 and PyTorch 2.0.1 with the finest tuning.
🚦 Traffic Management System 🚏 With Deep Reinforcement Learning 🚗
Performance evaluation of several DRL algorithms in a discrete action-space for resource allocation in Open RAN
Hosts my major and mini Deep Reinforcement learning 👨💻and Deep Learning projects 🔝
经典强化学习、深度强化学习算法复现
A modular, high-level Python package for Deep Reinforcement Learning, designed to simplify the implementation and study of DRL algorithms, offering an accessible and extensible framework for students, researchers, and developers.
Calibration and rl标定与强化学习
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.
This repo implements the REINFORCE algorithm for solving the Cart Pole V1 environment of the Gymnasium library using Python 3.8 and PyTorch 2.0.1.
Modular pytorch implementation of PPO including in depth commentary of implementation details!
A Scalable & Modular Networked Approach to TorchRL Environments for Quick DRL Development