Department of Computer Science
Washington & Lee University
CS397 (Fall 2002): Genetic Algorithms
Course instructor:
Prof. Simon Levy
(Parmly 407B, x8419,
levys@wlu.edu).
Office hours: MWF 2-4 and by appointment.
This page: http://www.cs.wlu.edu/~levy/cs397
Course Requirements
- Prereqs:
Programming competence (Java, C, or C++); a little theory (inductive proofs)
- Homework ("thought exercises" and coding)
- Final programming project (individual or team)
- Class participation: This is a seminar, and a goal
will be to have everyone present a paper or
unassigned section of the book, as well as a final project summary, if
we have time.
- Each of these three (homework, project, participation) will count
for approximately 1/3 of your final grade. This policy is flexible; for
example, if you have trouble with some of the problem sets but do an
outstanding final project, the project grade will count more.
PROBLEM SETS
Guidelines - please read
them carefully and be sure that you understand them.
FINAL PROJECT: Proposal Due Monday 16 October
This project can be as simple as replicating published results; for
example, implementing Hillis's sorting networks GA, or something
equally non-trivial. Or, more likely, it will be a research problem
from your own area of interest (math, geology, programming languages)
that you'd like to try and solve with a GA. The actual project should
take about a month of work, and be summarized in a 5-10 page writeup,
with references, that you will present to the class at the end of the
term.
LECTURE NOTES
06 September 2002
Postscript
PDF
(Intro, Course Outline)
09 September 2002
Postscript
PDF
(Crossover/Mutation, Fitness Landscapes, No Free Lunch)
11 September 2002
Postscript
PDF
(Prisoner's Dilemma, Sorting Networks)
13 September 2002
Postscript
PDF
(Schemas, Building Blocks)
15 September 2002
Postscript
PDF
(Genetic Programming)
20 September 2002
Postscript
PDF
(Cellular Automata)
23 September 2002
Postscript
PDF
(Intro. to Neural Networks)
25 September 2002
Postscript
PDF
(Evoloving Neural Networks)
27 September 2002
Postscript
PDF
(Evoloving a Learning Rule)
30 September 2002
Postscript
PDF
(The Baldwin Effect)
09 October 2002
Postscript
PDF
(Theoretical Foundations)
14 October 2002
Postscript
PDF
(When to use a GA; Encodings)
16 October 2002
Postscript
PDF
(Inversion; Hot Spots)
18 October 2002
Postscript
PDF
(The Messy GA; Selection Methods)
October - November 2002
Postscript
PDF
(Watson's SEAM Algorithm)
22 November 2002
Postscript
PDF
(MBOA: Multi-objective Bayesian Optimization Algorithm)
LINKS
-
AI Helps Gamers Keep on Playing
: Using a GA to learn a human player's strategy (Check out the nerd
in the byline!)
-
The DEMO Lab : My old stomping ground! Lots of cool GA-related
papers, interactive games, animations, etc.