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Engineering - Computational Intelligence and Complexity | Quantum Machine Intelligence

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Quantum Machine Intelligence

Quantum Machine Intelligence

Editor-in-Chief: Giovanni Acampora

ISSN: 2524-4906 (print version)
ISSN: 2524-4914 (electronic version)

Journal no. 42484

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  • The first scientific journal that highlights the synergies between quantum computing and artificial intelligence
  • Promotes a synthesis of the research areas of machine learning and data science, and their engineering applications based on quantum technologies
  • Fosters the application of quantum computing and artificial intelligence to address real-world problems

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.

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.

Related subjects » Applied & Technical Physics - Artificial Intelligence - Computational Intelligence and Complexity

Abstracted/Indexed in 

Google Scholar, ACM, EBSCO Discovery Service, Institute of Scientific and Technical Information of China, Japanese Science and Technology Agency (JST), Naver, OCLC WorldCat Discovery Service, ProQuest-ExLibris Primo, ProQuest-ExLibris Summon

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  • Aims and Scope

    Aims and Scope

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    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.

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