Tangles: a structural approach to artificial intelligence in the empirical sciences (Part I)
Year: 2020
Type: preprint
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.
Source: arXiv (Cornell University)
Author: Diestel, Reinhard
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4287765339