https://github.com/malolm/arc-genesis
A python framework to streamline your ARC challenge solutions. From graphical displays to optimized Kaggle submissions
https://github.com/malolm/arc-genesis
arc-agi kaggle-competition notebook python3
Last synced: 5 months ago
JSON representation
A python framework to streamline your ARC challenge solutions. From graphical displays to optimized Kaggle submissions
- Host: GitHub
- URL: https://github.com/malolm/arc-genesis
- Owner: MaloLM
- License: apache-2.0
- Created: 2024-10-03T15:39:00.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-17T12:13:44.000Z (12 months ago)
- Last Synced: 2025-05-05T04:14:48.358Z (5 months ago)
- Topics: arc-agi, kaggle-competition, notebook, python3
- Language: Jupyter Notebook
- Homepage:
- Size: 792 KB
- Stars: 13
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ARC Genesis 🚀
## What is ARC-AGI?
ARC-AGI (Abstraction and Reasoning Corpus for Artificial General Intelligence) is a benchmark that evaluates AI's ability to solve novel, abstract problems—key aspects of general intelligence according to ARC creators.
Unlike traditional benchmarks, ARC-AGI tests how well AI can generalize to new tasks, focusing on abstraction, reasoning, and pattern recognition through grid-based puzzles.
> Source: [arc-agi website](https://arcprize.org)
## What is ARC Genesis?
🌟 **ARC Genesis** is a Python framework built to help you working in the ARC-AGI contest by providing essential tools and resources. It enables you to:
- Visualize problems effectively.
- Deploy and evaluate solutions via Kaggle (2 methods).
- Optimize task execution order for better performance.
- Start small before scaling to complex challenges (like 30x30 grids).
## What is JupyterGenesis?
[JupyterGenesis](https://github.com/MaloLM/JupyterGenesis) simplifies setting up a Jupyter environment across platforms (Linux, macOS, Windows). It automates virtual environment creation and Python package installation.
### How to Use JupyterGenesis?
Simply run the script for your OS to install dependencies and launch a local JupyterLab server for your development needs.
> For more details, check the [documentation](./jupyter-genesis/README.md).
## Requirements
You only need `Python 3` and `pip`, under Linux, macOS, or Windows.
## Project Structure and Setup
After cloning the repository, you’ll access:
- **`challenges_plotting.ipynb`**: Visualizes ARC challenges with various graphical methods.
- **`challenges_sorting.ipynb`**: Optimizes task execution order during evaluations.
- **`tiny_arc.ipynb`**: Focuses on solving smaller, simpler tasks before scaling to larger ones.
- **`kaggle_submission.ipynb`**: Prepares solutions for submission using external package imports.
- **`self_sufficient_kaggle_submission.ipynb`**: Offers a self-contained submission method.
- **`local_benchmark.ipynb`**: Benchmarks your solutions locally.
## Kaggle Submission
Kaggle requires notebook submissions for evaluation. You can submit in two ways:
### 1. By Importing an External Package
This approach separates the solution and evaluation for cleaner development. Refer to `/source/kaggle_submission.ipynb`.
### 2. Using a Self-Sufficient Notebook
A quicker, all-in-one solution without external imports but with some limitations... Refer to `self_sufficient_kaggle_submission.ipynb`.
## Contribute! 🙌
Contributions are welcome from anyone! Whether it's code, documentation, translations, or bug reporting, every contribution helps us move closer to AGI.