# CS411: Non-Standard Computing

Unit 3: Genetic Algorithms   In this unit, we start with an overview of genetic algorithms.  Then, we show a practical example of genetic algorithms that demonstrate the application of event classification and feature selection.  Also, we show a video about computational systems that have been used for natural selection on complex artificial problems.

This unit will take approximately 13 hours to complete.

☐    Subunit 3.1: 3 hours

☐    Subunit 3.2: 4 hours

☐    Subunit 3.3: 3 hours

☐    Subunit 3.4: 2 hour

☐    Unit 3 Assessment: 1 hour

Unit3 Learning Outcomes
Upon successful completion of this unit, the student will be able to:

• Describe the functional principles of genetic algorithms.
• List the limitations genetic algorithms.
• List and describe the main methods to palliate problems arising in genetic algorithms.

3.1 Introduction to Genetic Algorithms   - Reading: www.rennard.org: Jean-Philippe Rennard’s “Introduction to Genetic Algorithms” Link: www.rennard.org: Jean-Philippe Rennard’s “Introduction to Genetic Algorithms” (HTML)

Instructions: Read this webpage for general overview of genetic algorithms.  This reading covers subunits 3.1.1 through 3.1.3.

Terms of Use: The linked material above has been reposted by the kind permission of Jean-Philippe Rennard, and can be viewed in its original from here.  Please note that this material is under copyright and cannot be reproduced in any capacity without explicit permission from the copyright holder.

3.1.1 Evolution and Optimization   3.1.2 Evolution and Genetic Algorithms   3.1.3 Functioning of a Genetic Algorithm   3.1.4 Adaptation and Selection: the Scaling Problem   3.2 Genetic Algorithm Classifiers   - Reading: McGill University: Gabriel Kevorkian and Marko Milek’s “Genetic Algorithm Classifiers”

``````Link: McGill University: Gabriel Kevorkian and Marko Milek’s
“[Genetic Algorithm
Classifiers](http://cgm.cs.mcgill.ca/%7Esoss/cs644/projects/marko/)”
(HTML and Java)

(7 pages).  Click on the “Next” button at the bottom of the text to
move on to each subsequent webpage.  Also, go through the example by
clicking on the 'Algorithm' and 'Applet' links at the top of the
webpage. The example demonstrates specific application of event
classification and feature selection.  This reading covers subunits
3.1.1 through 3.1.3 of this course.

displayed on the webpage above.
``````

3.2.1 Introduction   3.2.2 Classifiers   3.2.3 Algorithm   3.3 Evolutionary Algorithms   - Web Media: Videolectures.net: Adam Prügel-Bennett’s "Evolutionary Algorithms” Link: Videolectures.net: Adam Prügel-Bennett’s "Evolutionary Algorithms" (YouTube)

Instructions: Watch this video on computational systems that have been used for natural selection on complex artificial problems.  There have been some successes, but the complexity of artificially evolved systems remains short of the complexity one easily finds in biology.  You may benefit from viewing certain sections of this video more than once; repeat watching any sections of the video that are hard to follow.  It may also help to take notes as you view this video.  This should take approximately 2 hours of study time.