sjtudh
Follow
Stars
⛽️「算法通关手册」：超详细的「算法与数据结构」基础讲解教程，从零基础开始学习算法知识，850+ 道「LeetCode 题目」详细解析，200 道「大厂面试热门题目」。
This is the repository for the collection of surveys and reviews in communication and networking domains.
Source code for "Intelligent Reflecting Surface Configurations for Smart Radio Using Deep Reinforcement Learning", IEEE JSAC.
Methods and Implements of Deep Clustering
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
无线与深度学习结合的论文代码整理/Paper-with-Code-of-Wireless-communication-Based-on-DL
This repository includes the source code of the DL-based symbol-by-symbol and frame-by-frame channel estimators proposed in "A Survey on Deep Learning Based Channel Estimation in Doubly Dispersive …
🔥 经典编程书籍大全，涵盖：计算机系统与网络、系统架构、算法与数据结构、前端开发、后端开发、移动开发、数据库、测试、项目与团队、程序员职业修炼、求职面试等
A research oriented repository on the Security and Robustness of Deep Learning for Wireless Communication Systems
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
Joint Transmit Beamforming and Phase Shifts Design with Deep Reinforcement Learning
Implementation of Deepmind's LaserTag-v0 game in A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning(2017)
(POSTER SESSION) A study of spatial dynamics under prisoners' dilemma and hawk-dove games, by Sangman Jung and Sunmi Lee
Matlab implementation of some evolutionary dynamics from game theory, such as: replicator dynamics, smith dynamics, logit dynamics, and Brown-von Neumann-Nash.
Evolutionary game theory on scale free networks, in Chapel!
Implements the algorithms presented in "Fast Reinforcement learning for energy efficient wireless communications
An Open Source Machine Learning Framework for Everyone
Implementation of Single-Agent and Multi-Agent Reinforcement Learning Algorithms. MATLAB.
This is MATLAB scripts of the book "Multi-Agent_Machine_Learning".
Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
D2D communication as a multi-agents system, and power control is achieved by maximizing system capacity while maintaining the requirement of quality of service(QoS) from cellular users.
RIS-Codes-Collection: A Complete Collection contains the Codes for RIS(IRS) Researches.