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:
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 |