CS776 Evolutionary Computation

Sushil J. Louis

SEM 223 (784-4315)

January 22, 2007

http://www.cse.unr.edu/$\sim$sushil

TextBooks

• Required: David E. Goldberg, Genetic algorithms in search, optimization and machine learning, 1989, Addison-Wesley.

• Recommended: David Fogel, Evolutionary Computation Towards a new Philosophy of Machine Intelligence, 1995, IEEE Press.

• Recommended: John Holland, Adaptation in Natural and Artificial Systems, 1992, The MIT Press.

• Recommended: John Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, 1992, Bradford Books.

• Recommended: Melanie Mitchel, An Introduction to Genetic Algorithms, 1996, The MIT Press.

Office hours

• MW from 2:30 - 3:30.
• And by appointment. Send email to sushil@cse.unr.edu

Syllabus

I will introduce genetic and evolutionary computing algorithms and their theory in the first four or five weeks of the course. You can then work in teams on a mutually agreeable research problem or project. You are welcome to work on areas that interest you, but you need to talk to me first. This semester I am most interested in systems that combine genetic algorithms with case-based reasoning. Please talk to me soon about projects - the sooner you get started the better you will do. Here are possible project types.

There are several ways to do well in this class.

• Research: Do publishable research. If you don't know how to do research this course will also teach you how. You will investigate a research problem that I think I understand and to which I am reasonably sure a solution exists.

• Development: Develop an industrial strength prototype of the demos on my web page. Your code will implement the best known evolutionary algorithm for the problem at hand and will be runnable like the demos.

• Research and Development: Attack a well defined sub-problem (I know this problem can be solved and probably how to solve it) and put a demo of your work on the web.

Groups are possible (encouraged) but need my permission. Project presentations will be at the end of the semester. While working on your problem, you will be asked to find, read, and present papers pertaining to your problem, or that you find interesting. Become familiar with library and internet resources. In addition to your presentations, there will be research presentations from graduate students, faculty, and other speakers.

Finally, you will learn how to efficiently read technical papers, write technical reports, present technical work, and perform scientific research and development. I encourage and require enthusiastic class participation.

Please look in http://www.cse.unr.edu/~sushil for pointers to papers and other information useful for this course. I would like each of you to set up a web page and keep a pointer to your work (graphical and textual).

If you do not already have one, you will need to get an account on CS department machines. You will also have access to and an account on a cluster (gaspac.cse.unr.edu) running ROCKS.

Your grade will depend on assignments, presentations, and project reports. I will expect to see you after each presentation to discuss the presentation and assign you a grade. Any person or group producing publishable work gets an automatic A.

Your grade will be calculated from the following table.

Item	Percentage
Assignments	20%
Presentations	20%
Project and Report	60%

Communications

If I need to communicate with the class as group I'll be placing a notice on the class web page. You are required to check the website and your email every day - I will send email to your CS email address. Get yourself a cs account and implement mail forwarding if you need to. Other Internet resources can be found on the class web page

This is a research oriented class. Research projects or research and development projects that you start in this class will usually constitute the bulk of a Master's thesis or professional paper.

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CS776 Evolutionary Computation

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