Department of Electrical and
Computer Engineering

EEC 693 / 793

Special Topics: Genetic Algorithms

A Genetic Algorithm
(GA) is a model of machine learning which is based on the theory of biological
evolution. This is done by creating (within a computer) a population of
individuals represented by chromosomes. Each chromosome is a set of character
strings that is analogous to the chromosomes that we see in biological DNA. The
individuals in the population then go through a process of simulated evolution.
Genetic algorithms are used in a number of different application areas. One
example is multidimensional optimization problems in which the character string
of the chromosome can be used to encode the values for the different parameters
being optimized. In practice we can implement this genetic model of computation
by using arrays of bits or characters to represent the chromosomes. Simple bit
manipulation operations allow the implementation of mating, crossover,
mutation, and other biologically inspired operations. When the genetic algorithm
is implemented it is usually done in a manner that involves the following
cycle:

- Evaluate the fitness of all of the
individuals in the population.
- Create a new population by performing
operations such as crossover, reproduction, and mutation, on the population.
- Discard the old population.
- Repeat the previous steps using the new
population. Each sequence of steps is called a generation.

You can view the syllabus for the course on-line. This course relies on the use of MATLAB, which is a general purpose computing environment for engineering. You can find more information about MATLAB at the link below.

Use concepts from statistics to determine if an independent variable has an effect on the outcome of an experiment:

· Alexei Sharov’s statistical tables

Genetic programming Powerpoint presentation:

· GP.ppt (940 KB)

Homework assignments:

Test solutions:

· Quiz 1

· Quiz 2

· Quiz 3

· Exam

Department of Electrical and Computer Engineering

Last Revised: August 11, 2004