TY - GEN
T1 - Towards Model-Driven Engineering for Quantum AI
AU - Moin, Armin
AU - Challenger, Moharram
AU - Badii, Atta
AU - Günnemann, Stephan
N1 - Publisher Copyright:
© 2022 Gesellschaft fur Informatik (GI). All rights reserved.
PY - 2022
Y1 - 2022
N2 - Over the past decade, Artificial Intelligence (AI) has provided enormous new possibilities and opportunities, but also new demands and requirements for software systems. In particular, Machine Learning (ML) has proven useful in almost every vertical application domain. In the decade ahead, an unprecedented paradigm shift from classical computing towards Quantum Computing (QC), with perhaps a quantum-classical hybrid model, is expected. We argue that the Model-Driven Engineering (MDE) paradigm can be an enabler and a facilitator, when it comes to the quantum and the quantum-classical hybrid applications. This includes not only automated code generation, but also automated model checking and verification, as well as model analysis in the early design phases, and model-to-model transformations both at the design-time and at the runtime. In this paper, the vision is focused on MDE for Quantum AI, particularly Quantum ML for the Internet of Things (IoT) and smart Cyber-Physical Systems (CPS) applications.
AB - Over the past decade, Artificial Intelligence (AI) has provided enormous new possibilities and opportunities, but also new demands and requirements for software systems. In particular, Machine Learning (ML) has proven useful in almost every vertical application domain. In the decade ahead, an unprecedented paradigm shift from classical computing towards Quantum Computing (QC), with perhaps a quantum-classical hybrid model, is expected. We argue that the Model-Driven Engineering (MDE) paradigm can be an enabler and a facilitator, when it comes to the quantum and the quantum-classical hybrid applications. This includes not only automated code generation, but also automated model checking and verification, as well as model analysis in the early design phases, and model-to-model transformations both at the design-time and at the runtime. In this paper, the vision is focused on MDE for Quantum AI, particularly Quantum ML for the Internet of Things (IoT) and smart Cyber-Physical Systems (CPS) applications.
KW - artificial intelligence
KW - cyber-physical systems
KW - internet of things
KW - machine learning
KW - model-driven engineering
KW - quantum computing
UR - http://www.scopus.com/inward/record.url?scp=85139745024&partnerID=8YFLogxK
U2 - 10.18420/inf2022_95
DO - 10.18420/inf2022_95
M3 - Conference contribution
AN - SCOPUS:85139745024
T3 - Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
SP - 1121
EP - 1131
BT - INFORMATIK 2022 - Informatik in den Naturwissenschaften
A2 - Demmler, Daniel
A2 - Krupka, Daniel
A2 - Federrath, Hannes
PB - Gesellschaft fur Informatik (GI)
T2 - 2022 Informatik in den Naturwissenschaften, INFORMATIK 2022 - 2022 Computer Science in the Natural Sciences, INFORMATIK 2022
Y2 - 26 September 2022 through 30 September 2022
ER -