使用Drl来解决多智能体卸载问题

采用强化学习来实现计算卸载

强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/

Joint strategy design on edge computing offloading based on deep reinforcement learning

Source Code of QDRL: Queue-aware Online DRL for Computation Offloading in Industrial Internet of Things

I build this Mobile Edge Computation simulating environment all by myself, and use the costomized ddpg reinforcement learning algorithm to make offloading decision.

[IEEE TMC 2020] "Computation Offloading in Multi-Access Edge Computing: A Multi-Task Learning Approach" and [IEEE GlobeCom 2023] "A Multi-Head Ensemble Multi-Task Learning Approach for Dynamical Co…

[Infocom'22] Preemptive Migration Prediction Network for Proactive Fault Tolerant Edge Computing

Code for the paper On-Policy vs. Off-Policy Deep Reinforcement Learning for Resource Allocation in Open Radio Access Network

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

DeepNude源码，去水印，带三个模型文件下载地址(cm.lib,mm.lib,mn.lib)，附使用说明，即跑。

Paper publised in TNSM entitled "DRL-Based Long-Term Resource Planning for Task Offloading Policies in Multi-Server Edge Computing Networks"

This project utilizes deep reinforcement learning methods for computation offloading and resource allocation in edge computing systems.

Simulation code of our paper in IEEE Transactions on Mobile Computing: ''Towards Decentralized Task Offloading and Resource Allocation in User-Centric Mobile Edge Computing''

OPTI Toolbox

Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks

This project is the implementation of the research paper titled "Dynamic Request Scheduling Optimization in Mobile Edge Computing for IoT Applications"

Simulation code for multi-user offloading in edge computing newtorks

Simulation code for EdgeGO -- A resource sharing framework for 6G edge computing in massive IoT systems, https://ieeexplore.ieee.org/document/9375469/

Simulation code of our paper in IEEE Transactions on Cognitive Communications and Networking: ''Energy-Efficient Blockchain-enabled User-Centric Mobile Edge Computing''

Implementation of submitted papers about Mobile Edge Computing (MEC).

Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling sa…

Algorithm implementation for my Edge Computing-related papers.

Deep reinforcement learning for mobile edge computing