humemai-research 2.0.2.post2

A Machine With Human-Like Memory Systems

humemai

This repo hosts a package humemai, a human-like memory systems that are modeled with knowledge knoweldge graphs (KGs). At the moment they are nothing but a Python list of RDF quadruples, but soon it'll be a better object type so that they can be compatible with graph databases, e.g., RDFLib, GraphDB, Neo4j, etc. Making it compatible with RDFLib is top priority and it'll come with v2. There have been both academic papers and applications that have used this package.

Installation

pip install humemai

python>=3.8

List of academic papers that use HumemAI

• "A Machine With Human-Like Memory Systems"
• "A Machine with Short-Term, Episodic, and Semantic Memory Systems"
• "Leveraging Knowledge Graph-Based Human-Like Memory Systems to Solve Partially Observable Markov Decision Processes"

List of applications that use HumemAI

pdoc documentation

Click on this link to see the HTML rendered docstrings

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Run make test && make style && make quality in the root repo directory, to ensure code quality.
4. Commit your Changes (git commit -m 'Add some AmazingFeature')
5. Push to the Branch (git push origin feature/AmazingFeature)
6. Open a Pull Request

License

MIT

Authors

• Taewoon Kim