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Biologically based machine learning paradigms: an introductory course

Author:

Adel M. AbunawassAuthors Info & Claims

ACM SIGCSE Bulletin, Volume 24, Issue 1

Pages 87 - 91

https://doi.org/10.1145/135250.134529

Published: 01 March 1992 Publication History

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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Cited By

Paxton J(1995)A novel approach to teaching artificial intelligenceACM SIGCSE Bulletin10.1145/199691.19982227:1(283-286)Online publication date: 15-Mar-1995
https://dl.acm.org/doi/10.1145/199691.199822
Paxton JLaxer C(1995)A novel approach to teaching artificial intelligenceProceedings of the twenty-sixth SIGCSE technical symposium on Computer science education10.1145/199688.199822(283-286)Online publication date: 15-Mar-1995
https://dl.acm.org/doi/10.1145/199688.199822

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Biologically based machine learning paradigms: an introductory 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

Editor:
James E. Miller
Univ. of Southern Mississippi, Hattiesburg, MS

Issue’s Table of Contents

SIGCSE '92: Proceedings of the twenty-third SIGCSE technical symposium on Computer science education
March 1992
332 pages
ISBN:0897914686
DOI:10.1145/134510
Chairman:
Nell B. Dale
Univ. of Texas, Austin

Copyright © 1992 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 01 March 1992

Published in SIGCSE Volume 24, Issue 1

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Cited By

Paxton J(1995)A novel approach to teaching artificial intelligenceACM SIGCSE Bulletin10.1145/199691.19982227:1(283-286)Online publication date: 15-Mar-1995
https://dl.acm.org/doi/10.1145/199691.199822
Paxton JLaxer C(1995)A novel approach to teaching artificial intelligenceProceedings of the twenty-sixth SIGCSE technical symposium on Computer science education10.1145/199688.199822(283-286)Online publication date: 15-Mar-1995
https://dl.acm.org/doi/10.1145/199688.199822

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