Computational infrastructure for concepts discovery in science and technology

Yaron Hakuk, Yoram Reich

Research output: Contribution to journalArticlepeer-review

Abstract

Automated scientific discovery, a topic in artificial intelligence has mainly been used to generate scientific insight from data. Our work follows the knowledge-driven discovery approach and introduces the use of category theory as the foundation for modeling diverse engineering fields represented with combinatorial representation. We show how category theory provides support for all stages of the discovery process starting from modeling the engineering knowledge. We demonstrate the use of the approach to rediscover previous discoveries in mechanics and discover new devices, some of which need to be realized to be appreciated. Category theory allows expanding the process to disciplines not modeled with combinatorial representations. We intend to demonstrate this in future studies.

Original languageEnglish
Article number101938
JournalAdvanced Engineering Informatics
Volume56
DOIs
StatePublished - Apr 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

Keywords

  • Category theory
  • Combinatorial representations
  • Duality
  • IEKG
  • Knowledge-driven discovery

Fingerprint

Dive into the research topics of 'Computational infrastructure for concepts discovery in science and technology'. Together they form a unique fingerprint.

Cite this