dawei_wei's repositories
ardupilot
ArduPlane, ArduCopter, ArduRover source
ardupilot-1
一个电赛项目，实现stm32连接apm、openmv、arduino
AVIATOR
Python script that simulates downlink and uplink UAV data traffic based on the traffic models derived from actual UAV data
baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
Constraint_RL_MPC
Safe control of unknown dynamic systems with reinforcement learning and model predictive control
CrowdNav
Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning
Deep-reinforcement-learning-with-pytorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
delphi
A Cryptographic Inference Service for Neural Networks
dqn-multi-agent-rl
Deep Q-learning (DQN) for Multi-agent Reinforcement Learning (RL)
DROO
Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks
edu.ufc.femtost.disc.sysml2modelica
ATL and Acceleo based transformation from SysML to Modelica
Flight_maddpg
Maddpg_flight code
hector_quadrotor
hector_quadrotor contains packages related to modeling, control and simulation of quadrotor UAV systems.
MARL-Papers
Paper list of multi-agent reinforcement learning (MARL)
Multi-Uav-Mission-Planner
It is a module that enables the user to control multiple UAV's from one GCS(MP)
Nash-DQN
Deep Reinforcement Learning for Nash Equilibria
per
Prioritized Experience Replay (PER) implementation in PyTorch
PettingZoo
Gym for multi-agent reinforcement learning
Quad-Sim
A package of documentation and software supporting MATLAB/Simulink based dynamic modeling and simulation of quadcopter vehicles for control system design
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
reward-sharing-nash-q
Reconstruct Structured Rewards in Mixed Cooperative MARL
universe-starter-agent
A starter agent that can solve a number of universe environments.