This is the source code of the paper titled "QMR: Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks".

wsnet

The Computer Vision Research Toolkit

QMR implementation using DroNet

Packet routing simulation on a dynamic network using Shortest Path Routing, Q-learning, and Deep Q-learning

Dueling DQN Pytorch

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)

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

This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are…

very easy implementation of dueling DQN in pytorch

Deep Reinforcement Learning with DQN, Double DQN, Dueling DQN, Noisy Net (Noisy DQN), and DQN with Prioritized Experience Replay

Reinforcement Learning | tensorflow implementation of DQN, Dueling DQN and Double DQN performed on Atari Breakout

Tensorflow + OpenAI Gym implementation of Deep Q-Network (DQN), Double DQN (DDQN), Dueling Network and Deep Deterministic Policy Gradient (DDPG)

Vanilla DQN, Double DQN, and Dueling DQN implemented in PyTorch

Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51