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Biologically based machine learning paradigms: an introductory course

Published:01 March 1992Publication History
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Abstract

This paper describes an introductory course on biologically based sub-symbolic machine learning paradigms. Specifically, this paper covers Artificial Neural Networks, Genetic Algorithms and Genetics-Based Machine Learning. It provides the structure, motivation, content, texts and tools for the course. This course is suitable for an upper division undergraduate level course or as an introductory graduate course. The paper includes a section on bibliographical references to aid the instructor in preparing for this course.

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          • Published in

            cover image ACM SIGCSE Bulletin
            ACM SIGCSE Bulletin  Volume 24, Issue 1
            March 1992
            313 pages
            ISSN:0097-8418
            DOI:10.1145/135250
            Issue’s Table of Contents
            • cover image ACM Conferences
              SIGCSE '92: Proceedings of the twenty-third SIGCSE technical symposium on Computer science education
              March 1992
              332 pages
              ISBN:0897914686
              DOI:10.1145/134510

            Copyright © 1992 ACM

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            • Published: 1 March 1992

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