About this Journal

Aims and Scope

Machine Intelligence is areas in software engineering and computer science where soft computing and machine intelligence are solutions to computationally hard tasks. Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. Machine Intelligence explores virtually all aspects of machine learning, including deep learning and more classical algorithms. Machine Learning is based on Artificial Neural Networks, Support Vector Machines, Classification and Regression Trees, and some more similar methods. Important is that the resulting mathematical models are built by training from example data instead of being constructed analytically. This means that they are example-based or empirical mathematical models instead of analytical ones. This special issue provides a new forum for the dissemination of knowledge on both theoretical and applied research on machine learning with an ultimate aim to bridge the gap between these two disciplines of knowledge. It focuses on technologies that support interaction between the above two bodies of knowledge and fosters unified development in next generation computational models for machine intelligence.

Bibliographical Information

ISSN: TBD (Print)
ISSN: TBD (Online)
DOI: 10.46410

Open Access

Journal of Machine Systems, Intelligence, and Simulations is a journal with free access. Upon posting, all documents are automatically accessible for reading. You will find more detail on our position on Open Access on our copyright agreement.


Publication and Dates

Published: Semi – Annually

Submission Guidelines

Paper Format (Doc)
Copyright (PDF)



  • Become a Reviewer
  • To Oder
  • Open Access Publishing
  • Call For Paper
  • Special Issue

Related Journal