LNNs are a novel Neuro = Symbolic
framework designed to seamlessly provide key
properties of both neural nets (learning) and symbolic logic (knowledge and reasoning).
To install the LNN:
conda create -n lnn python=3.9 -y
conda activate lnn
master
branch to keep up to date with the latest supported features:
pip install git+https://github.com/IBM/LNN
Contributions to the LNN codebase are welcome!
Please have a look at the contribution guide for more information on how to set up the LNN for contributing and how to follow our development standards.
Read the Docs | Academic Papers | Educational Resources | Neuro-Symbolic AI | API Overview | Python Module |
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If you use Logical Neural Networks for research, please consider citing the reference paper:
@article{riegel2020logical,
title={Logical neural networks},
author={Riegel, Ryan and Gray, Alexander and Luus, Francois and Khan, Naweed and Makondo, Ndivhuwo and Akhalwaya, Ismail Yunus and Qian, Haifeng and Fagin, Ronald and Barahona, Francisco and Sharma, Udit and others},
journal={arXiv preprint arXiv:2006.13155},
year={2020}
}