ai-agent

mec_morl_multipolicy: Smart Edge Computing

Name: mec_morl_multipolicy: Smart Edge Computing
Author: gracefulning

Mobile edge computing with deep reinforcement learning for founders. Python code from research paper.

From the repo · “The python code for paper "Multi-objective Deep Reinforcement Learning for Mobile Edge Computing"”

126 stars16 forksPythonGuide quality 8/10 · reviewed Jul 2Updated 7/4/2023100% free · open source

What it does

Optimizes mobile edge computing performance using deep reinforcement learning with multiple policies

When to use it

•When you need to balance competing objectives like latency, throughput, and energy efficiency in mobile edge computing
•When you have limited resources and need to prioritize tasks based on their importance and deadlines
•When you want to improve the scalability and adaptability of your mobile edge computing system

Ready-to-paste prompt

python main.py --train --num-policies 3 --objective latency,throughput --learning-rate 0.001

Heads up: Make sure you have the correct versions of Python and required libraries, as specified in the requirements.txt file, to avoid compatibility issues

Saves to your device

Use with Claude

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✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/mec-morl-multipolicy && curl -fsSL https://workflowstacks.com/api/skills/mec-morl-multipolicy/claude-skill -o ~/.claude/skills/mec-morl-multipolicy/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How mec_morl_multipolicy: Smart Edge Computing works

Codeflow

Free to inspect

Mec_morl_multipolicy: Smart Edge Computing is a small Python project (~850 lines across 5 code files). Setup is light: small project — see the README for how to run it. Last commit 40 months ago, MIT license, no tests found.

Size

Small codebase

~850 lines · 5 code files · 7 min skim

Setup

Light setup

Small project — see the README for how to run it.

Runs on

Python

No API keys detected

Python 100%

Where to start reading

1
README.md
Start here — what it does and how to install it

What's in each folder

env/Folder3 files

network/Folder2 files

READMENo tests foundThin docsNo CIMIT licenseLast update 40 mo ago