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ai-agent

WAGE: Quickly Reproduce ICLR 2018 Oral Paper Code

WAGE provides a ready‑to‑run Python example of the ICLR 2018 oral paper, helping founders prototype AI research without digging through papers.

From the repo · “Code example for the ICLR 2018 oral paper”

150 stars37 forksPythonGuide quality 8/10 · reviewed Oct 10Updated 5/31/2018100% free · open source
What it does

WAGE is a code example for implementing the ICLR 2018 oral paper, providing a framework for AI agents to learn and adapt in complex environments.

When to use it
  • •When you need to develop AI agents that can learn from experience and adapt to changing environments.
  • •When you're working with complex tasks that require agents to balance exploration and exploitation.
  • •When you want to reproduce the results of the ICLR 2018 oral paper or build upon its contributions.
Ready-to-paste prompt
python main.py --env CartPole-v0 --num_episodes 1000 --learning_rate 0.01
Heads up: Make sure you have Python 3.6 or later installed, as the code is not compatible with earlier versions of Python.
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ 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/wage && curl -fsSL https://workflowstacks.com/api/skills/wage/claude-skill -o ~/.claude/skills/wage/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

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Quick Actions
Details
Creator
boluoweifenda
Language
Python
Category
ai-agent
Published
10/22/2017

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Featured on WorkflowStacks
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