Open Access Policy

Machine Learning for Human Intelligence (MLHI) is committed to the principles of open access to ensure that high-quality scientific knowledge is freely available to the global research community. The journal supports the vision of the Budapest Open Access Initiative (BOAI), which promotes unrestricted access to scholarly research.

All articles published in MLHI are freely accessible online without subscription or payment. Readers are permitted to read, download, copy, distribute, print, search, or link to the full text of articles for any lawful purpose without financial, legal, or technical barriers. This approach enhances the visibility, accessibility, and impact of research in machine learning, artificial intelligence, and human-centered technologies.

Author Self-Archiving Policy

MLHI supports the dissemination of research through institutional and personal repositories. Authors are permitted to archive the accepted manuscript (post-print) and/or the final published version (publisher’s PDF) on their institutional repositories, personal websites, or academic platforms without any embargo period, provided that proper citation and acknowledgment of the journal are included.

Copyright and Licensing

Upon acceptance of a manuscript, authors are required to sign a Copyright Transfer Agreement, granting the journal the right to publish and distribute the work. However, authors retain the right to reuse their material for academic and educational purposes, including:

  • Institutional repositories

  • Academic presentations

  • Theses and dissertations

  • Classroom teaching and lectures

All articles published in Machine Learning for Human Intelligence (MLHI) are distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, reproduction, and adaptation in any medium, including commercial use, provided that the original work and source are properly credited.

Commitment to Open Science

Through its open access policy, MLHI aims to promote global collaboration, transparency, and knowledge sharing in the fields of machine learning and human intelligence. By removing access barriers, the journal ensures that researchers, practitioners, educators, and policymakers worldwide can benefit from the latest scientific developments.

For further information regarding the journal’s policies, please contact the editorial office at editor@mlhi.org.