Home > Research > Publications & Outputs > Towards Anthropomorphic Machine Learning

Electronic data

  • CO_COMSI-2018-05-0087.R1_Gu

    Rights statement: ©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

    Accepted author manuscript, 1 MB, PDF document

Links

Text available via DOI:

View graph of relations

Towards Anthropomorphic Machine Learning

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>09/2018
<mark>Journal</mark>IEEE Computer
Issue number9
Volume51
Number of pages10
Pages (from-to)18-27
Publication statusPublished
Original languageEnglish

Abstract

In this paper, we introduce and discuss the concept of anthropomorphic machine learning as an emerging direction for the future development in the area of artificial intelligence (AI) and data science. We start with outlining research challenges and opportunities, which the contemporary landscape offers. We focus on machine learning, statistical learning, deep learning and computational intelligence as theoretical and methodological areas of greater promise for breakthrough results and underpinning the future revolutionary changes in technology development as well as in our everyday life and societies. Our critical analysis brings us to the open problems and we formulate the paradigm shift in the understanding of machine learning. In a nutshell, our vision for the next generational machine learning methods and algorithms is anthropomorphic, which resembles the way people/humans learn from data. This concept brings machine learning from the statistics to the area of computational intelligence and AI.

Bibliographic note

©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.