ILASP

At ILASP, we build Logic-based Machine Learning systems, which learn highly expressive rules that can be translated into plain English. Logic-based systems have several advantages over other forms of machine learning, namely: Generalisation: Logic-based systems can generalise from very few examples, making it possible to learn complex knowledge without needing large datasets. Interpretability: As the learned knowledge can be translated into English, it can be explained to users and verified/corrected where necessary. Ability to incorporate existing knowledge: Logic-based systems do not need to learn everything from scratch, and can instead start from an existing knowledge base, containing anything known before the learning starts or even previously learned rules.