KI - Künstliche Intelligenz - CfP Special Issue: Quantum AI

Quantum Artificial Intelligence (QAI) refers to the use of quantum computing and quantum communication for solving computational problems in AI, and vice versa. While binary and probabilistic at the input and output, quantum computing uses nonclassical principles such as superposition and entanglement to speed up or otherwise enhance computations. Albeit non-intuitive, quantum theory is well-established in a mathematical framework and thoroughly tested. This framework allows the use of quantum principles for computation with the quantum gate model as well as with quantum annealing. In principle, quantum computing can go beyond its classical counterpart in terms of possible computational speed-up for problems in NP making use of exponential state representations and unitary operations.
In the past decade, QAI research proposed quite a few quantum and hybrid quantum-classical algorithms for various tasks of machine learning, coordination in multiagent systems, optimization, and natural language processing. Many of these have shown some experimental evidence, hinting at the potential of unattainably better performance in speed-up and solution quality compared to the best classical solution methods for the problem at hand. The ongoing quest for further feasible QAI solutions for practical applications with potential quantum advantage is actually gaining interest also from industries such as finance, automotive, space, health, and chemistry. On the other hand, there has been tremendous progress in developing real quantum computers in the current noisy intermediate-scale quantum era. Some of these quantum processing units are publicly accessible via the Internet through frameworks for quantum programming and evaluation. However, it remains to be seen when QAI algorithms for what kind of real-world application services actually become available and profitable to prosumers.

This special issue aims at providing an overview of QAI regarding, but not limited to, the following topics:

• Use of quantum computing for machine learning, natural language processing, automated planning, knowledge representation and reasoning
• Use of quantum computing for multiagent systems
• Use of quantum AI solutions for practical applications in industries such as finance, chemistry, automotive, space, health
• Use of AI techniques for enabling quantum computing

Submission is closed.

All articles undergo double-blind peer reviewing.

Contacts:

Matthias Klusch (DFKI, matthias.klusch@dfki.de)

Jörg Lässig (HS Zittau-Görlitz, joerg.laessig@iosb-ast.fraunhofer.de)

Frank Wilhelm-Mauch (FZ Jülich, f.wilhelm-mauch@fz-juelich.de)