MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence
Abstract
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.
Cite
@article{arxiv.2107.06708,
title = {MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence},
author = {Armin Moin and Moharram Challenger and Atta Badii and Stephan Günnemann},
journal= {arXiv preprint arXiv:2107.06708},
year = {2022}
}
Comments
GI Quantum Computing Workshop - INFORMATIK 2022