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

Journal information

Editors-in-Chief
  • Xi-Zhao Wang,
  • Daniel S. Yeung
Publishing model
Hybrid (Transformative Journal). Learn about publishing Open Access with us

Journal metrics

3.753 (2019)
Impact factor
3.140 (2019)
Five year impact factor
69 days
Submission to first decision
251 days
Submission to acceptance
142,602 (2020)
Downloads

Latest articles

This journal has 18 open access articles

Subscribe

eJournal
$79.00
Note this is only the net price. Taxes will be calculated during checkout.
  • Immediate online access with complete access to all articles starting 1997
  • Downloadable in PDF format
  • Subscription expires 12/31/2021

About this journal

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

Rights and permissions

Springer policies

© Springer-Verlag GmbH Germany, part of Springer Nature