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Instructor: Tauritz, Daniel R.
Email: tauritzd@mst.edu

Comp Sci 5401: Evolutionary Computing

Introduces evolutionary algorithms, a class of stochastic, population-based algorithms inspired by natural evolution theory (e.g., genetic algorithms), capable of solving complex problems for which other techniques fail. Students will implement course concepts, tackling science, engineering and/or business problems.
Additional Info:

CompSci5401-Syllabus


Time/Day: 09:30 am - 10:45 am TR
Prerequisites: A "C" or better grade in both Comp Sci 2500 and in a Statistics course.
Units: 3
Course Component(s): Lecture
Meet Your Instructor: Bio
Introduction Video: Intro
Group Project: no
Live Participation Required: no
Download Restrictions: allowed upon request
Books:

A.E. Eiben and J.E. Smith, Introduction to Evolutionary Computing, Second Edition, Springer, 2015, ISBN 978-3-662-44873-1 [Companion website: https://proxy.qualtrics.com/proxy/?url=http%3A%2F%2Fevolutionarycomputation.org&token=5wlIaHanko2cDb014urY1q6PiTSI5CKak6cjTyppBc0%3D]


Attention Distance Students

For classes produced by I.T. MediaServices: Access to live and archived media will be available in MediaSpace at mst.mediaspace.kaltura.com or in Panopto at mst.hosted.panopto.com. For more information email itms@mst.edu.
For other course content: please contact your instructor.

Enrollment Information
Campus Delivery Mode Class Status Class Nbr Section
Distance Education Internet OPEN 76852 1DIS

Course Access Information
Learning Management System Canvas