Cybernetics is concerned with describing complex interactions and interrelationships between systems which are omnipresent in our daily life. Machine Learning discovers fundamental functional relationships between variables and ensembles of variables in systems. The merging of the disciplines of Machine Learning and Cybernetics is aimed at the discovery of various forms of interaction between systems through diverse mechanisms of learning from data.

The International Journal of Machine Learning and Cybernetics (IJMLC) focuses on the key research problems emerging at the junction of machine learning and cybernetics and serves as a broad forum for rapid dissemination of the latest advancements in the area. The emphasis of IJMLC is on the hybrid development of machine learning and cybernetics schemes inspired by different contributing disciplines such as engineering, mathematics, cognitive sciences, and applications. New ideas, design alternatives, implementations and case studies pertaining to all the aspects of machine learning and cybernetics fall within the scope of the IJMLC.

Key research areas to be covered by the journal include:

  • Machine Learning for modeling interactions between systems
  • Pattern Recognition technology to support discovery of system-environment interaction
  • Control of system-environment interactions
  • Biochemical interaction in biological and biologically-inspired systems
  • Learning for improvement of communication schemes between systems
Editors-in-Chief
  • Xi-Zhao Wang,
  • Daniel S. Yeung
Publishing model
Hybrid. Open Choice – What is this?
Impact
Impact factor: 3.844 (2018)
Five year impact factor: 2.918 (2018)
Speed
Submission to first decision: 61 days
Acceptance to publication: 11 days
Usage
Downloads: 92,715 (2018)

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About this journal

Electronic ISSN
1868-808X
Print ISSN
1868-8071
Abstracted and indexed in
  1. ACM Digital Library
  2. Chemical Abstracts Service (CAS)
  3. EBSCO Discovery Service
  4. EI Compendex
  5. Google Scholar
  6. INSPEC
  7. Institute of Scientific and Technical Information of China
  8. Japanese Science and Technology Agency (JST)
  9. Journal Citation Reports/Science Edition
  10. Naver
  11. OCLC WorldCat Discovery Service
  12. ProQuest Advanced Technologies & Aerospace Database
  13. ProQuest Central
  14. ProQuest SciTech Premium Collection
  15. ProQuest Technology Collection
  16. ProQuest-ExLibris Primo
  17. ProQuest-ExLibris Summon
  18. SCImago
  19. SCOPUS
  20. Science Citation Index Expanded (SciSearch)
  21. WTI Frankfurt eG
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