A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems

Authors

  • Frank van Harmelen Department of Computer Science, Vrije Universiteit Amsterdam, Netherlands
  • Annette ten Teije Department of Computer Science, Vrije Universiteit Amsterdam, Netherlands

Keywords:

Hybrid systems, neurosymbolic systems, knowledge representation, machine learning, design patters

Abstract

We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation. As in other areas of computer science (knowledge engineering, software engineering, ontology engineering, process mining and others), such design patterns help to systematize the literature, clarify which combinations of techniques serve which purposes, and encourage re-use of software components. We have validated our set of compositional design patterns against a large body of recent literature.

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Author Biographies

Frank van Harmelen, Department of Computer Science, Vrije Universiteit Amsterdam, Netherlands

Frank van Harmelen is professor of Knowledge Representation and Reasoning at the VU University Amsterdam, and adjunct professor at Wuhan University and Wuhan University of Science and Technology. He played a leading role in the development of the Semantic Web, which aims to make data on the web semantically interpretable by machines through formal representations. He was a contributor to the Web Ontology Language OWL, now a standard in worldwide commercial use, and the basis for an entire research community. He is one of the architects of the semantic storage engine Sesame (now RDF4J). This work received the 10-year impact award of the Semantic Web community. He co-authored the Semantic Web Primer, the first text book on the semantic web (now translated into 5 languages), and he co-edited the standard reference work in his field (The Handbook of Knowledge Representation). He is a member of the Royal Netherlands Academy of Arts and Sciences, the Royal Holland Academy of Sciences, and Academia Europea, and fellow of the European Association for Artificial Intelligence.

Annette ten Teije, Department of Computer Science, Vrije Universiteit Amsterdam, Netherlands

Annette ten Teije is an associate professor at the Vrije Universiteit Amsterdam. Her interests are in knowledge modelling, representation and reasoning in particular in the medical domain. She earned a PhD (1997) from the University of Amsterdam (SWI) for her thesis entitled “Automated configuration of problem solving methods in diagnosis”. She was involved in a number of EU-funded projects IBROW project under the FET-O programme, Protocure-II project, concerned with formal modelling and verification of medical guidelines and protocols, WS-DIAMOND FET-Open project concerned with self-healing web-services, FP7-ICT EURECA project concerned with enabling information re-use by linking clinical research and clinical care. She was program co-chair for the 18th International Conference on Knowledge Engineering and Knowledge Management (2012), and was the general chair of the 16th conference on Artificial Intelligence in Medicine.

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