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Logic-based Machine Learning and 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:


An animation explaining the need for Logic-based Machine Learning.


Our main system, ILASP (Inductive Learning of Answer Set Programs), which gave the company its name, learns knowledge expressed in the language of Answer Set Programming (ASP). ILASP's ability to learn full ASP programs, compared with previous approaches that could only learn a very restricted subset of ASP, has opened up a variety of new applications that were previously out of scope for Logic-based Machine Learning systems.

Example applications of ILASP

ILASP was designed to be a general system without a specific application domain in mind, meaning that it can be applied to many different domains. We have described a few of the previous applications of ILASP in the sections below to give an idea of what it can be used for. The list is by no means exhaustive, and you can find further example applications in our research papers.