1. Proceedings
  2. I3M
  3. 2019
  4. EMSS
  5. 10.46354/i3m.2019.emss.017

Artificial intelligence: concept overview, methodological approaches and choice metrics

  • a Michael Bogner  ,
  • b Martin Steiger  ,
  • c Franz Wiesinger  ,
  • a,b,c University of Applied Sciences Upper Austria – Embedded Systems Design, Softwarepark 11, A-4232 Hagenberg, Austria
Cite as
Bogner M., Steiger M., Wiesinger F. (2019). Artificial intelligence: concept overview, methodological approaches and choice metrics. Proceedings of the 31st European Modeling & Simulation Symposium (EMSS 2019), pp. 103-110. DOI: https://doi.org/10.46354/i3m.2019.emss.017.

Abstract

During the last couple of years there has been a renaissance in the field of artificial intelligence, also called AI. A wide diversity of possible concepts to this topic leads to the compulsion to be properly informed about a variety of approaches. This paper focuses on explaining the primary and most relevant theoretical concepts in regard to artificial intelligence and to rate them based on derived criteria. To achieve this, the most significant manifestations of these learning concepts are analyzed to identify their core characteristics. Choice metrics are derived based on this knowledge and selected with regard to an industrial environment. Additionally, a methodical approach is developed to ease the user’s choice of an appropriate concept according to the given criteria. The final result of this paper is a set of diagrams that illustrate the different artificial intelligence concepts based on the found criteria.

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