Tangles: a structural approach to artificial intelligence in the empirical sciences (Part I)
Abstract
Traditional clustering identifies groups of objects that share certain qualities. Tangles do the converse: they identify groups of qualities that often occur together. They can thereby discover, relate, and structure types: of behaviour, political views, texts, or viruses. If desired, tangles can also be used as a new method for traditional clustering. They offer a precise, quantitative paradigm suited particularly to fuzzy clusters, since they do not require any assignment of objects to the clusters which these collectively form. This is the first of four parts of a book with the above title. The book explores applications outside mathematics of the notion and theory of tangles generalised from the graph tangles know from graph minor theory.
Cite
@article{arxiv.2006.01830,
title = {Tangles: a structural approach to artificial intelligence in the empirical sciences (Part I)},
author = {Reinhard Diestel},
journal= {arXiv preprint arXiv:2006.01830},
year = {2024}
}
Comments
The print edition of the book will appear later this year with CUP. An enhanced eBook edition and open-source software, with tutorials, are available already from tangles-book.com