TY - GEN
T1 - Artificial intelligence
T2 - 31st European Modeling and Simulation Symposium, EMSS 2019
AU - Bogner, Michael
AU - Steiger, Martin
AU - Wiesinger, Franz
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Decision support system
KW - Deep learning
KW - Independent metrics
UR - http://www.scopus.com/inward/record.url?scp=85073809530&partnerID=8YFLogxK
U2 - 10.46354/i3m.2019.emss.017
DO - 10.46354/i3m.2019.emss.017
M3 - Conference contribution
AN - SCOPUS:85073809530
T3 - 31st European Modeling and Simulation Symposium, EMSS 2019
SP - 103
EP - 110
BT - 31st European Modeling and Simulation Symposium, EMSS 2019
A2 - Affenzeller, Michael
A2 - Bruzzone, Agostino G.
A2 - Longo, Francesco
A2 - Pereira, Guilherme
PB - DIME UNIVERSITY OF GENOA
Y2 - 18 September 2019 through 20 September 2019
ER -