A System for Accessible Artificial Intelligence.

Randal S. Olson, Moshe Sipper, William G. La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu, Patryk Orzechowski, Ryan J. Urbanowicz, John H. Holmes, Jason H. Moore

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

While artificial intelligence (AI) has become widespread, many commercial AI systems are not yet accessible to individual researchers nor the general public due to the deep knowledge of the systems required to use them. We believe that AI has matured to the point where it should be an accessible technology for everyone. We present an ongoing project whose ultimate goal is to deliver an open source, user-friendly AI system that is specialized for machine learning analysis of complex data in the biomedical and health care domains. We discuss how genetic programming can aid in this endeavor, and highlight specific examples where genetic programming has automated machine learning analyses in previous projects.
Original languageEnglish GB
Title of host publicationGenetic programming theory and practice XV
EditorsW. Banzhaf , R. Olson, W. Tozier , R. Riolo
PublisherSpringer
Pages121-134
ISBN (Electronic)978-3-319-90512-9
ISBN (Print)978-3-319-90511-2
DOIs
StatePublished - 2017

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