CSCS Workshop: Introduction to Genetic Programming (fwd)
Maxim K Zalota
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Date: Tue, 14 Nov 2000 14:44:26 -0500 (EST)
From: Rick Riolo <r...@fiore.physics.lsa.umich.edu>
Reply-To: rlr...@umich.edu
To: complex systems reading group discussions <csrg-d...@egroups.com>,
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Fall 2000 CSCS 501 <cscs5...@egroups.com>
Subject: CSCS Workshop: Introduction to Genetic Programming
Resent-Date: Tue, 14 Nov 2000 14:43:14 -0500
Resent-From: systems_...@eecs.umich.edu
Title: Introduction to Genetic Programming
Date: Tuesday 28 November
Time: 3:10 - 5:00 pm
Place: 4246 Randall Lab Bldg.
Genetic Programming (GP), one type of Evoluationary Algorithm, uses
the ideas of natural selection to create computer programs that solve
user- specified problems. That is, an initial population of randomly
generated computer programs are evaluated to rate how well they solve
the problem at hand. The better programs are allowed to reproduce and
the programs which do not solve the problem as well are eliminated.
Most importantly, variation is introduced into the offspring programs
by allowing their parent programs to "mate" (i.e., exchange
sub-programs). Many variants are worse than the parents, but a
surprising number are also better at solving the problem. This
generational process is repeated, with the best programs at each
generation becoming better and better at solving the problem, until
the user is satisfied (or runs out of computer time!).
Surprisingly, genetic programming has been shown to solve a wide
variety of standard problems encountered in the machine learning
literature. GP has been applied to many different kinds of problems,
including pattern recognition and classification, robot control,
neural net design and learning, induction and regression problems, and
even the creation of art. Most recently, there is much effort
applying GP to "real world" problems.
This workshop will begin with an introduction to the basic ideas of
GP, including how problems and the programs that solve them are
represented and how the underlying genetic algorithm works to select
and recombine programs. Handouts will include references to
sources of further information, including information and software
packages available via the Internet.
This workshop is free and open to everyone, but
please send email to psc...@umich.edu to register.
----------------------------------------------------------
Rick Riolo rlr...@umich.edu
Center for Study of Complex Systems (CSCS)
4477 Randall Lab
University of Michigan Ann Arbor MI 48109-1120
Phone: 734 763 3323 Fax: 734 763 9267
http://www.pscs.umich.edu/PEOPLE/rlr-home.html