Stars
Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-model, multi-channel. Lightweight, extensible, one-line install. (f...
[EMNLP 2025 Demo] PDF scientific paper translation with preserved formats - 基于 AI 完整保留排版的 PDF 文档全文双语翻译,支持 Google/DeepL/Ollama/OpenAI 等服务,提供 CLI/GUI/MCP/Docker/Zotero
Modularized Implementation of Deep RL Algorithms in 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)
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
Ryu component-based software defined networking framework
This page is for the SlimYOLOv3: Narrower, Faster and Better for UAV Real-Time Applications
🔥机器学习/深度学习/Python/大模型/多模态/LLM/deeplearning/Python/Algorithm interview/NLP Tutorial
Tien Kung-Lab: Direct IsaacLab Workflow for Legged Robots
🔥数据可视化,大屏, 支持Echarts,SQL,API,VUE,可用于Jupyter, 比pyecharts容易, 极低门槛,拿来即用,比拖拽方便,项目插件或独立平台皆可, 简单, 敏捷, 高效, 通用化, 高度可定制化,为你完全打通前后端, 图形数据联动, 筛选开发毫无压力, 数据缓存处理机制让报表快人一步
Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks
Emulator for Software-Defined Wireless Networks
UavNetSim: A Python-based simulation platform for designing and testing communication protocols and control algorithms in UAV swarm.
随着移动云计算和边缘计算的快速发展,以及人工智能的广泛应用,产生了边缘智能(Edge Intelligence)的概念。深度神经网络(例如CNN)已被广泛应用于移动智能应用程序中,但是移动设备有限的存储和计算资源无法满足深度神经网络计算的需求。神经网络压缩与加速技术可以加速神经网络的计算,例如剪枝、量化、卷积核分解等。但是这些技术在实际应用非常复杂,并且可能导致模型精度的下降。在移动云计算或...
Code for paper "Adaptive Federated Learning in Resource Constrained Edge Computing Systems"
muzixing / ryu
Forked from faucetsdn/ryuLi Cheng's self-defined Ryu.
UAV Flight Simulator for Reinforcement Learning Research
自动读取本地pdf文献并提取标题、作者、摘要和结论生成综述。Read and translate English literature to generate review automatically.
Datasets for data-driven deep reinforcement learning with PyBullet environments
Code for Intelligent Dynamic Data Offloading in a Competitive Mobile Edge Computing Market paper https://www.mdpi.com/1999-5903/11/5/118/pdf
A quadcopter simulator with single and multi-quad simulations
Research on incentive mechanism design in mobile crowdsensing and mobile edge computing by deep reinforcement learning approaches.
Source code of the paper "Deep Reinforcement Learning-Based Online Resource Management for UAV-Assisted Edge Computing With Dual Connectivity," in IEEE/ACM Transactions on Networking, Apr. 2023.
An Edge-computing platform based on Wi-Fi routers
A python package of Cross-edge Computation Offloading (CCO) algorithm and its distributed version, Decor for Mobile Edge Computing (MEC).
learning based mobile edge computing simulator
The purpose of this project is to introduce an Adaptive RO Model for QoS-aware SDNs using DRL that dynamically considers various QoS parameters to generate a dynamic action-reward strategy.