Aims and scope

Quantum Machine Intelligence publishes original articles on cutting-edge experimental and theoretical research in all areas of quantum artificial intelligence. The Journal is unique in promoting a synthesis of machine learning, data science and computational intelligence research with quantum computing developments. Its primary goal is to foster the utilization of quantum computing for real-world problems so as to pave the way towards the next generation of artificial intelligence systems. The Journal also publishes innovative papers reporting on machine intelligence theories, methods and applications inspired by physics and nature, e.g. computational intelligence, fuzzy systems, evolutionary computation, machine and deep learning.

Selected areas and topics of interest include, but are not limited to:

1) Quantum Machine Learning

2) Quantum Computing for Artificial Intelligence

3) Artificial Intelligence for Quantum Information Processing

4) Quantum and Bio-inspired Computational Intelligence

5) Quantum Annealing and Optimization

All papers submitted undergo a rigorous peer review to ensure their originality, timeliness, relevance and readability. The journal also welcomes occasional review articles and short communications in all of the above-mentioned topic areas.