ai-agent

mec_morl_multipolicy: Smart Edge Computing

Mobile edge computing with deep reinforcement learning. Python code from research paper.
125 stars16 forksPythonGuide quality 8/10Updated 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
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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

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Details
Creator
gracefulning
Language
Python
Category
ai-agent
Published
7/4/2023

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