phil610351 Goto Github PK

drl-gnn

drl4ec

drl_experiment

drl_rsma_radar_uav

drl_uav_cellularnet

Simulator developed for the mobility management of UAV base stations project featuring A3C

drl_zhengbingkun

droo

Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks

dynamic-request-scheduling-optimization-in-mobile-edge-computing-for-iot-applications

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

dynamicmultichannelrl

Contains Implementation of Paper " S Wang, H Liu, P H Gomes, and B Krishnamachari ; Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks"

edge-computing-codes

edge-computing-codes-1

Simulation of algorithms for Edge Computing-related papers.

edge-offloading

computation offloading in mobile edge computing using Reinforcement Learning

emorl-tcto

An implementation of EMORL-TCTO algorithm.

energy-harvesting-ddpg-

Codes for "Deep Deterministic Policy Gradient (DDPG) based Energy Harvesting Wireless Communications"

eua-dataset

Edge server, user dataset for Edge Computing research

facmac

fcmnet

fed-mec

This project is focused on the design, development, and deployment of federated solutions to problems in the framework of mobile edge computing.

fed-mf-mal

This is the code for paper: Scalable Federated Multi-agent Architecture forNetworked Communication Scenarios

fedadapt

Adaptive Offloading of Federated Learning on IoT Devices

federated-double-deep-q_network-

A framework that exploits the potentials of distributed federated learning and double deep Q-networks to minimize joint energy and delay in IoT networks

federated-learning-pytorch

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

fen

FEN Code

fleetai

fmlp-rec

further

Source code for "Influencing Long-Term Behavior in Multiagent Reinforcement Learning" (NeurIPS 2022)

game-theoretic-deep-reinforcement-learning

Code of Paper "Joint Task Offloading and Resource Optimization in NOMA-based Vehicular Edge Computing: A Game-Theoretic DRL Approach", JSA 2022.

gan-ddqn

gats-for-traffic-signal-control

gcs_aamas337

The code for AAMAS2022 《GCS: Graph-based Coordination Strategy for Multi-Agent Reinforcement Learning》