Computational Intelligence for Changing Environments [Guest Editorial]

Hussain, Amir; Tao, Dacheng; Wu, Jonathan; Zhao, Dongbin

Abstract

The articles in this special section focus on the growing interest in biologically inspired learning (BIL), which refers to a wide range of learning techniques, motivated by biology, that try to mimic specific biological functions or behaviors.

Citation

Hussain, A., Tao, D., Wu, J., & Zhao, D. (2015). Computational Intelligence for Changing Environments [Guest Editorial]. IEEE Computational Intelligence Magazine, 10(4), 10-11. https://doi.org/10.1109/MCI.2015.2472119

• Journal Article Type: Editorial
• Acceptance Date: Oct 1, 2015
• Online Publication Date: Oct 12, 2015
• Publication Date: 2015-11
• Deposit Date: Oct 10, 2019
• Journal: IEEE Computational Intelligence Magazine
• Print ISSN: 1556-603X
• Electronic ISSN: 1556-6048
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 4
• Pages: 10-11
• DOI: https://doi.org/10.1109/MCI.2015.2472119
• Keywords: Biological system modeling, Learning systems, Behavioral science
• Public URL: http://researchrepository.napier.ac.uk/Output/1792866