🚀 Optimize your portfolio with deep reinforcement learning, achieving superior returns and risk management in dynamic asset allocation.

🚀 Integrate PX4, ROS 2, and Gazebo for drone SLAM, mapping, and control with LiDAR and RGBD camera support in simulation.

Custom gym environment for training Deep Reinforcement Learning policies to race and drift on 1/10 scale or full-size Ackermann vehicles. SB3 and wandb integration. Based on the f1tenth_gym simulator built by UPenn

基于深度强化学习的多智能体协作任务调度系统

Machine learning library, Distributed training, Deep learning, Reinforcement learning, Models, TensorFlow, PyTorch

Practice the Deep Reinforcement Learning (DRL) with the gym on laptop.

An elegant PyTorch deep reinforcement learning library.

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.

Reliable Policy Transfer for Safety-Aware End-to-End Driving with Deep Reinforcement Learning

🇺🇾 Uruguayan Truco game engine + library written entirely in Python

Repository that houses the program used to investigate the control of subsystems in homes based on a DRL model. The program uses the EnergyPlus Python API and Ray's Tune and RLlib libraries.

A DRL SAC policy based XAUUSD trading bot

A Deep Reinforcement Learning (PPO) model exported for optimizing VM placement and lifecycle management. Developed by UCD for the EU MLSysOps project.

Setup for working with SO-101 robot arm based on LeRobot library

Mode for optimizing 5G networks latency. Developed by NTT DATA for the EU MLSysOps project.

A Deep Reinforcement Learning (DRL) solution for the Job Scheduling Problem using PPO and Stable Baselines3. Optimized to minimize makespan by balancing workloads across machines in a custom OpenAI Gym environment, outperforming standard heuristic baselines.

A Resource-Constrained Project Scheduling Agent (RCPSA) based on GNN, e-greedy DQN, and model-based planning

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

Calibration and rl标定与强化学习

Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"