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From: David.Beasley@cm.cf.ac.uk (David Beasley)
Subject: FAQ: comp.ai.genetic part 5/6 (A Guide to Frequently Asked Questions)
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Followup-To: comp.ai.genetic
Summary: This is part 5 of a entitled "The Hitch-Hiker's Guide to
Evolutionary Computation". A periodically published list of
Frequently Asked Questions (and their answers) about Evolutionary
Algorithms, Life and Everything. It should be read by anyone who
whishes to post to the comp.ai.genetic newsgroup, preferably *before*
posting.
Originator: David.Beasley@cm.cf.ac.uk (David Beasley)
Sender: David.Beasley@cm.cf.ac.uk (David Beasley)
Supersedes:
Organization: University of Wales College of Cardiff, Cardiff, WALES, UK.
References:
Date: Tue, 20 Sep 94 09:06:24 GMT
Approved: news-answers-request@MIT.Edu
Expires: 23 Dec 1994 09:04:52 GMT
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Archive-name: ai-faq/genetic/part5
Last-Modified: 9/20/94
Issue: 2.3
TABLE OF CONTENTS OF PART 5
Q20: What EA software packages are available?
Q20.1: Free software packages?
Q20.2: Commercial software packages?
Q20.3: Current research projects?
----------------------------------------------------------------------
Subject: Q20: What EA software packages are available?
This gives a list of all known EA software packages available to the
public. The list was originally maintained by Nici Schraudolph. In
June '93 it was agreed that it would be incorporated into this FAQ
and the responsibility for maintenance taken over by the FAQ editor.
A copy of most of the packages described below are kept at ENCORE,
(See Q15.3), available by anonymous FTP.
Most GENETIC PROGRAMMING software is archived by Jim McCoy
. Available by FTP in:
ftp.cc.utexas.edu:/pub/genetic-programming/ directory there are
subdirectories containing papers related to GP, archives of the
mailing list, as well as a suite of programs for implementing GP.
These programs include the Lisp code from Koza's "Genetic
Programming" [KOZA92], as well as implementations in C and C++, as
for example SGPC: Simple Genetic Programming in C by Walter Alden
Tackett and Aviram Carmi .
A survey paper entitled "Genetic Algorithm Programming Environments"
was published in IEEE Computer in the February 1994 issue. Written
by Filho, Alippi and Treleaven of University College, London, UK.
It's available by FTP as
bells.cs.ucl.ac.uk:/papagena/game/docs/gasurvey.ps
PLEASE NOTE
For many of these software packages, specific ordering instructions
are given in the descriptions below (see Q20.1, Q20.2, Q20.3).
Please read and follow them before unnecessarily bothering the listed
author or contact! Also note that these programs haven't been
independently tested, so there are no guarantees of their quality.
A major revision was undertaken in August 1994, when all authors were
contacted, and asked to confirm the accuracy of the information
contained here. A few authors did not respond to the request for
information. These are noted below by: (Unverified 8/94). In these
cases, FTP address were checked by the FAQ editor, to confirm that
this information (at least) is correct. In two cases, email to the
author bounced back as "undeliverable" -- these are noted below.
Legend
Type (this is a very ad-hoc classification)
GE: generational GA
SS: steady-state GA
PA: (pseudo) parallel GA
ES: evolution strategy
OO: object-oriented
XP: expert system
ED: educational/demo
CF: classifier system
OS Operating System; X11 implies Unix; "Win" means Microsoft
Windows 3.x/NT (PC); "DOS" means MS-DOS or compatibles.
Lang Programming Language; in parentheses: source code not included;
"TPas" = Think Pascal, "OPas" = MPW Object Pascal
Price
(1) free to government contractors, $221 otherwise, (2)
educational discount available, (3) available as addendum to a
book, (4) single 1850 DM, site license 5200 DM, (5) single 200
DM, site license 500 DM, (6) free for academic and educational
use.
Author or Contact
given as Internet e-mail address if possible
ES/GA/XP System Implementations:
=========================================================================
Name Type OS Lang Price Author/Contact
=========================================================================
BUGS GE, X11, C free Joshua Smith
ED Suntools
DGenesis GE, Unix C free Erick Cantu-Paz
PA,ED
DOUGAL SS, DOS Turbo free Brett Parker
GE Pascal
ESCaPaDE ES Unix C free Frank Hoffmeister
Evolution GE, DOS C free Hans-Michael Voigt and
Machine ES Joachim Born
GAC, GE Unix C free Bill Spears
GAL " " Lisp "
GAGA GE Unix C free Jon Crowcroft
GAGS GE, Unix, C++ free JJ Merelo
SS,OO DOS
GALOPPS GE, Unix, C free Erik Goodman
PA DOS
GANNET GE, Unix C free Darrell Duane
NN
GAucsd GE Unix C free Nici Schraudolph
GA GE, DOS (C++) free Mark Hughes
Workbench ED
GECO GE, Unix, Lisp free George P. W. Williams, Jr.
OO,ED MacOS
Genesis GE, Unix, C free John Grefenstette
ED DOS
GENEsYs GE Unix C free Thomas Baeck
GenET SS, Unix, C free Cezary Z. Janikow
ES,ED X, etc.
Genie GE Mac TPas free Lance Chambers
Genitor SS Unix C free Darrell Whitley
GENlib SS Unix, C (6) Jochen Ruhland
GENOCOP GE Unix C free Zbigniew Michalewicz
GIGA SS Unix C free Joe Culberson
LibGA GE, Unix/DOS C free Art Corcoran
SS,ED NeXT/Amiga
LICE ES Unix, C free Joachim Sprave
DOS
mGA GE Unix C, free Dave Goldberg
Lisp
PARAGenesis PA, CM C* free Michael van Lent
GE
PGA PA, Unix, C free Peter Ross
SS,GE etc.
SGA-C, GE Unix C free Robert E. Smith
SGA-Cube nCube
Splicer GE Mac, C (1) Steve Bayer
X11
TOLKIEN OO, Unix, C++ free Anthony Yiu-Cheung Tang
GE DOS
WOLF SS Unix C free David Rogers
=========================================================================
Classifier System Implementations:
=========================================================================
Name Type OS Lang Price Author/Contact
=========================================================================
CFS-C CF, Unix/DOS C free Rick Riolo
ED
SCS-C CF, Unix/DOS C free Joerg Heitkoetter
ED Atari TOS
==========================================================================
Commercial Packages:
=========================================================================
Name Type OS Lang Price Author/Contact
=========================================================================
EnGENEer OO, X11 C ? George Robbins,
GA Logica Cambridge Ltd.
EvoFrame/ OO, Mac, C++/ (4,2) Optimum Software
REALizer ES DOS OPas (5,2)
Evolver GE DOS, (C, $345 Phil Rybeck, Axcelis Inc.
Mac Pascal)
GAME OO, X11 C++ (3) Jose R. Filho
GA
MicroGA/ OO, Mac, C++ $249 Emergent Behavior, Inc.
Galapagos SS Win (2)
Omega ? DOS ? ? David Barrow, KiQ Ltd.
OOGA OO, Mac, Lisp $60 Lawrence Davis
GE DOS
PC/Beagle XP DOS ? 69UKP Richard Forsyth
XpertRule/XP DOS (TPas) 995UKP Attar Software
GenAsys
XYpe SS Mac (C) $725 Ed Swartz, Virtual Image Inc.
=========================================================================
------------------------------
Subject: Q20.1: Free software packages?
BUGS:
BUGS (Better to Use Genetic Systems) is an interactive program for
demonstrating the GENETIC ALGORITHM and is written in the spirit of
Richard Dawkins' celebrated Blind Watchmaker software. The user can
play god (or `GA FITNESS function,' more accurately) and try to
evolve lifelike organisms (curves). Playing with BUGS is an easy way
to get an understanding of how and why the GA works. In addition to
demonstrating the basic GENETIC OPERATORs (SELECTION, CROSSOVER, and
MUTATION), it allows users to easily see and understand phenomena
such as GENETIC DRIFT and premature convergence. BUGS is written in C
and runs under Suntools and X Windows.
BUGS was written by Joshua Smith at Williams
College and is available by FTP from
santafe.edu:/pub/misc/BUGS/BUGS.tar.Z and from
ftp.aic.nrl.navy.mil:/pub/galist/src/ga/BUGS.tar.Z Note that it is
unsupported software, copyrighted but freely distributable. Address:
Room E15-492, MIT Media Lab, 20 Ames Street, Cambridge, MA 02139.
(Unverified 8/94).
DGenesis:
DGenesis is a distributed implementation of a Parallel GA. It is
based on Genesis 5.0. It runs on a network of UNIX workstations. It
has been tested with DECstations, microVAXes, Sun Workstations and
PCs running 386BSD 0.1. Each subpopulation is handled by a UNIX
process and the communication between them is accomplished using
Berkeley sockets. The system is programmed in C and is available free
of charge by anonymous FTP from lamport.rhon.itam.mx:/ and from
ftp.aic.nrl.navy.mil:/pub/galist/src/ga/dgenesis-1.0.tar.Z
DGenesis allows the user to set the MIGRATION interval, the migration
rate and the topology between the SUB-POPULATIONs. There has not
been much work investigating the effect of the topology on the
PERFORMANCE of the GA, DGenesis was written specifically to encourage
experimentation in this area. It still needs many refinements, but
some may find it useful.
Contact Erick Cantu-Paz at the
Instituto Tecnologico Autonomo de Mexico (ITAM)
Dougal:
DOUGAL is a demonstration program for solving the TRAVELLING SALESMAN
PROBLEM using GAs. The system guides the user through the GA,
allowing them to see the results of altering parameters relating to
CROSSOVER, MUTATION etc. The system demonstrates graphicaly the
OPTIMIZATION of the route. The options open to the user to
experiment with include percentage CROSSOVER and MUTATION, POPULATION
size, steady state or generational replacement, FITNESS technique
(linear normalised, is evaluation, etc).
DOUGAL requires an IBM compatible PC with a VGA monitor. The
software is free, however I would appreciate feedback on what you
think of the software.
Dougal is available by FTP from ENCORE (see Q15.3) in file
EC/GA/src/dougal.zip It's pkzipped and contains executable, vga
driver, source code and full documentation. It is important to place
the vga driver (egavga.bgi) in the same directory as DOUGAL. Author:
Brett Parker, 7 Glencourse, East Boldon, Tyne + Wear, NE36 0LW,
England.
ESCaPaDE:
ESCaPaDE is a sophisticated software environment to run experiments
with Evolutionary Algorithms, such as e.g. an EVOLUTION STRATEGY.
The main support for experimental work is provided by two internal
tables: (1) a table of objective functions and (2) a table of so-
called data monitors, which allow easy implementation of functions
for monitoring all types of information inside the Evolutionary
Algorithm under experiment.
ESCaPaDE 1.2 comes with the KORR implementation of the EVOLUTION
STRATEGY by H.-P. Schwefel which offers simple and correlated
MUTATIONs. KORR is provided as a FORTRAN 77 subroutine, and its
cross-compiled C version is used internally by ESCaPaDE.
An extended version of the package was used for several
investigations so far and has proven to be very reliable. The
software and its documentation is fully copyrighted although it may
be freely used for scientific work; it requires 5-6 MB of disk space.
In order to obtain ESCaPaDE, please send a message to the e-mail
address below. The SUBJECT line should contain 'help' or 'get
ESCaPaDE'. (If the subject lines is invalid, your mail will be
ignored!). For more information contact: Frank Hoffmeister, Systems
Analysis Research Group, LSXI, Department of Computer Science,
University of Dortmund, D-44221 Dortmund, Germany. Net:
Evolution Machine:
The Evolution Machine (EM) is universally applicable to continuous
(real-coded) OPTIMIZATION problems. In the EM we have coded
fundamental evolutionary algorithms (GENETIC ALGORITHMs and
EVOLUTION STRATEGIEs), and added some of our approaches to
evolutionary search.
The EM includes extensive menu techniques with:
o Default parameter setting for unexperienced users.
o Well-defined entries for EM-control by freaks of the EM, who
want to leave the standard process control.
o Data processing for repeated runs (with or without change of the
strategy parameters).
o Graphical presentation of results: online presentation of the
EVOLUTION progress, one-, two- and three-dimensional graphic
output to analyse the FITNESS function and the evolution process.
o Integration of calling MS-DOS utilities (Turbo C).
We provide the EM-software in object code, which can be run on PC's
with MS-DOS and Turbo C, v2.0, resp. Turbo C++,v1.01. The Manual to
the EM is included in the distribution kit.
The EM software is available by FTP from ftp-bionik.fb10.tu-
berlin.de:/pub/software/Evolution-Machine/ This directory contains
the compressed files em_tc.exe (Turbo C), em_tcp.exe (Turbo C++) and
em_man.exe (the manual). There is also em-man.ps.Z, a compressed
PostScript file of the manual. If you do not have FTP access, please
send us either 5 1/4 or 3 1/2 MS-DOS compatible disks. We will return
them with the compressed files (834 kB).
Official contact information: Hans-Michael Voigt or Joachim Born,
Technical University Berlin, Bionics and EVOLUTION Techniques
Laboratory, Bio- and Neuroinformatics Research Group, Ackerstrasse
71-76 (ACK1), D-13355 Berlin, Germany. Net: <{voigt,born}@fb10.tu-
berlin.de> (Unverified 8/94).
GAC, GAL:
Bill Spears writes: These are packages I've
been using for a few years. GAC is a GA written in C. GAL is my
Common Lisp version. They are similar in spirit to John
Grefenstette's Genesis, but they don't have all the nice bells and
whistles. Both versions currently run on Sun workstations. If you
have something else, you might need to do a little modification.
Both versions are free: All I ask is that I be credited when it is
appropriate. Also, I would appreciate hearing about improvements!
This software is the property of the US Department of the Navy.
The code will be in a "shar" format that will be easy to install.
This code is "as is", however. There is a README and some
documentation in the code. There is NO user's guide, though (nor am I
planning on writing one at this time). I am interested in hearing
about bugs, but I may not get around to fixing them for a while.
Also, I will be unable to answer many questions about the code, or
about GAs in general. This is not due to a lack of interest, but due
to a lack of free time!
Available by FTP from
ftp.aic.nrl.navy.mil:/pub/galist/src/ga/GAC.shar.Z and GAL.shar.Z .
PostScript versions of some papers are under "/pub/spears". Feel
free to browse.
GAGA:
GAGA (GA for General Application) is a self-contained, re-entrant
procedure which is suitable for the minimization of many "difficult"
cost functions. Originally written in Pascal by Ian Poole, it was
rewritten in C by Jon Crowcroft. GAGA can be obtained by request from
the author: Jon Crowcroft , Univeristy College
London, Gower Street, London WCIE 6BT, UK, or by FTP from
ftp://cs.ucl.ac.uk:/darpa/gaga.shar
GAGS:
GAGS 0.92 (Genetic Algorithms from Granada, Spain) is a library and
companion programs written and designed to take the heat out of
designing a GENETIC ALGORITHM. It features a class library for
genetic algorithm programming, but, from the user point of view, is a
genetic algorithm application generator. Just write the function you
want to optimize, and GAGS surrounds it with enough code to have a
genetic algorithm up and running, compiles it, and runs it. GAGS Is
written in C++, so that it can be compiled in any platform running
this GNU utility. It has been tested on various machines.
Documentation is available.
GAGS includes:
o Steady-state, roulette-wheel, tournament and elitist SELECTION.
o FITNESS evaluation using training files.
o Graphics output through gnuplot.
o Uniform and 2-point CROSSOVER, and bit-flip and gene-transposition
MUTATION.
o Variable length CHROMOSOMEs and related operators.
The application generator gags.pl is written in perl, so this
language must also be installed before GAGS. Available by FTP from:
kal-el.ugr.es:/pub/GAGS-0.92.tar.gz The programmer's manual is in the
same directory, file gagsprogs.ps.gz. GAGS is also available from
ENCORE (see Q15.3) in file EC/GA/src/gags-0.92.tar.gz with
documentation in EC/GA/docs/gagsprog.ps.gz
Maintained by J.J. Merelo, Grupo Geneura, Univ. Granada
GALOPPS:
GALOPPS (Genetic Algorithm Optimized for Portability and Parallelism)
is a flexible, generic GA, based upon SGA-C. It has been extended to
provide three types of island parallelism, ranging from a single PC
simulating parallel subpopulations, to multiple computers on a
network. It's been tested on a wide variety of DOS and UNIX
machines. An 80-page User Guide is provided.
GALOPPS extends the SGA capabilities several fold:
o 5 SELECTION methods.
o Random or superuniform initialization of binary CHROMOSOMEs.
o 3 CROSSOVER routines for value-based representations, and 4 for
order-based reps.
o 3 MUTATION routines.
o 4 FITNESS scaling routines.
o Various replacement strategy options, including crowding
replacement and new incest-reduction option.
o Elitism is optional.
o Convergence: lost, converged, percent converged, etc.
o Various PERFORMANCE measures
o Uses "SGA philosophy" of one template file for the user to modify,
but enriched with many additional user callbacks, for added
flexibility, extensibility.
Ten sample applications are provided -- "standard" ones are
Goldberg's three examples, Holland's Royal Road "Challenge" problem,
and a blind traveling salesperson problem.
For portability, the user interface in the standard distribution is
non-graphical. A number of GUIs are in development.
GALOPPS Release 2.20 and manual v2.20.ps are available by FTP from
isl.cps.msu.edu:/pub/GA/GALOPPS2.20/
Contact: Erik Goodman, Genetic Algorithms Research and Applications
Group (GARAGe), Computer Science and Case Center for Computer-Aided
Engineering and Manufacturing, 112 Engineering Building, Michigan
State University, East Lansing 48824.
GANNET:
GANNET (Genetic Algorithm / Neural NETwork) is a software package
written by Jason Spofford in 1990 which allows one to evolve neural
networks. It offers a variety of configuration options related to
rates of the GENETIC OPERATORs. GANNET evolves nets based upon three
FITNESS functions: Input/Output Accuracy, Output 'Stability', and
Network Size.
The evolved neural network presently has a binary input and binary
output format, with neurodes that have either 2 or 4 inputs and
weights ranging from -3 to +4. GANNET allows for up to 250 neurodes
in a net. Research using GANNET is continuing and a new version will
be released in late 1994 / early 1995.
GANNET is available by FTP from fame.gmu.edu:/gannet/source/ There
are separate directories for GANNET itself, a verifier program which
verifies the best neural network generated (/gannet/verifier), and
some sample datasets (/gannet/datasets). Further, Spofford's masters
thesis descrribing GANNET is available in postscript format
(/gannet/thesis).
Contact: Darrell Duane or Dr. Kenneth Hintz, George Mason University,
Dept. of Electrical & Computer Engineering, Mail Stop 1G5, 4400
University Drive, Fairfax, VA 22033-4444 USA. Net:
or
GAucsd:
GAucsd is a Genesis-based GA package incorporating numerous bug fixes
and user interface improvements. Major additions include a wrapper
that simplifies the writing of evaluation functions, a facility to
distribute experiments over networks of machines, and Dynamic
Parameter Encoding, a technique that improves GA PERFORMANCE in
continuous SEARCH SPACEs by adaptively refining the genomic
representation of real-valued parameters.
GAucsd was written in C for Unix systems, but the central GA engine
is easily ported to other platforms. The entire package can be ported
to systems where implementations of the Unix utilities "make", "awk"
and "sh" are available.
GAucsd is available by FTP from cs.ucsd.edu:/pub/GAucsd/GAucsd14.sh.Z
or from ftp.aic.nrl.navy.mil:/pub/galist/src/ga/GAucsd14.sh.Z To be
added to a mailing list for bug reports, patches and updates, send
"add GAucsd" to .
Cognitive Computer Science Research Group, CSE Department, UCSD 0114,
La Jolla, CA 92093-0114, USA. Net:
GA Workbench:
A mouse-driven interactive GA demonstration program aimed at people
wishing to show GAs in action on simple FUNCTION OPTIMIZATIONs and to
help newcomers understand how GAs operate. Features: problem
functions drawn on screen using mouse, run-time plots of GA
POPULATION distribution, peak and average FITNESS. Useful population
STATISTICS displayed numerically, GA configuration (population size,
GENERATION gap etc.) performed interactively with mouse.
Requirements: MS-DOS PC, mouse, EGA/VGA display.
Available by FTP from the simtel20 archive mirrors, e.g. wsmr-
simtel20.army.mil:/pub/msdos/neurlnet/gaw110.zip or
wuarchive.wustl.edu: or oak.oakland.edu: Produced by Mark Hughes
. A windows version is in preparation.
GECO:
GECO (Genetic Evolution through Combination of Objects) is an
extensible, object-oriented framework for prototyping GENETIC
ALGORITHMs in Common Lisp. GECO makes extensive use of CLOS, the
Common Lisp Object System, to implement its functionality. The
abstractions provided by the classes have been chosen with the intent
both of being easily understandable to anyone familiar with the
paradigm of genetic algorithms, and of providing the algorithm
developer with the ability to customize all aspects of its operation.
It comes with extensive documentation, in the form of a PostScript
file, and some simple examples are also provided to illustrate its
intended use.
GECO Version 2.0 is available by FTP. See the file
ftp.aic.nrl.navy.mil:/pub/galist/src/ga/GECO-v2.0.README for more
information.
George P. W. Williams, Jr., 1334 Columbus City Rd., Scottsboro, AL
35768. Net: .
Genesis:
Genesis is a generational GA system written in C by John
Grefenstette. As the first widely available GA program Genesis has
been very influential in stimulating the use of GAs, and several
other GA packages are based on it. Genesis is available together with
OOGA (see below), or by FTP from
ftp.aic.nrl.navy.mil:/pub/galist/src/ga/genesis.tar.Z (Unverified
8/94).
GENEsYs:
GENEsYs is a Genesis-based GA implementation which includes
extensions and new features for experimental purposes, such as
SELECTION schemes like linear ranking, Boltzmann, (mu,
lambda)-selection, and general extinctive selection variants,
CROSSOVER operators like n-point and uniform crossover as well as
discrete and intermediate RECOMBINATION. SELF-ADAPTATION of MUTATION
rates is also possible.
A set of objective functions is provided, including De Jong's
functions, complicated continuous functions, a TSP-problem, binary
functions, and a fractal function. There are also additional data-
monitoring facilities such as recording average, variance and skew of
OBJECT VARIABLES and MUTATION rates, or creating bitmap-dumps of the
POPULATION.
GENEsYs 1.0 is available via FTP from lumpi.informatik.uni-
dortmund.de:/pub/GA/src/GENEsYs-1.0.tar.Z The documentation alone is
available as /pub/GA/docs/GENEsYs-1.0-doc.tar.Z
For more information contact: Thomas Baeck, Systems Analysis Research
Group, LSXI, Department of Computer Science, University of Dortmund,
D-44221 Dortmund, Germany. Net: (Unverified 8/94).
GenET:
GenET is a "generic" GA package. It is generic in the sense that all
problem independent mechanisms have been implemented and can be used
regardless of application domain. Using the package forces (or
allows, however you look at it) concentration on the problem: you
have to suggest the best representation, and the best operators for
such space that utilize your problem-specific knowledge. You do not
have to think about possible GA models or their implementation.
The package, in addition to allowing for fast implementation of
applications and being a natural tool for comparing different models
and strategies, is intended to become a depository of representations
and operators. Currently, only floating point representation is
implemented in the library with few operators.
The algorithm provides a wide selection of models and choices. For
example, POPULATION models range from generational GA, through
steady-state, to (n,m)-EP and (n,n+m)-EP models (for arbitrary
problems, not just parameter OPTIMIZATION). (Some are not finished
at the moment). Choices include automatic adaptation of operator
probabilities and a dynamic ranking mechanism, etc.
Even though the implementation is far from optimal, it is quite
efficient - implemented in ATT's C++ (3.0) (functional design) and
also tested on gcc. Along with the package you will get two
examples. They illustrate how to implement problems with
heterogeneous and homogeneous structures, with explicit rep/opers and
how to use the existing library (FP). Very soon I will place there
another example - our GENOCOP operators for linearly constrained
OPTIMIZATION. One more example soon to appear illustrates how to
deal with complex structures and non-stationary problems - this is a
fuzzy rule-based controller optimized using the package and some
specific rep/operators.
If you start using the package, please send evaluations (especially
bugs) and suggestions for future versions to the author.
GenET Version 1.00 is available by FTP from
radom.umsl.edu:/var/ftp/GenET.tar.Z To learn more, you may get the
User's Manual, available in compressed postscript in
"/var/ftp/userMan.ps.Z". It also comes bundled with the complete
package.
Cezary Z. Janikow, Department of Math and CS, CCB319, St. Louis, MO
63121, USA. Net:
Genie:
Genie is a GA-based modeling/forecasting system that is used for
long-term planning. One can construct a model of an ENVIRONMENT and
then view the forecasts of how that environment will evolve into the
future. It is then possible to alter the future picture of the
environment so as to construct a picture of a desired future (I will
not enter into arguments of who is or should be responsible for
designing a desired or better future). The GA is then employed to
suggest changes to the existing environment so as to cause the
desired future to come about.
Genie is available free of charge via e-mail or on 3.5'' disk from:
Lance Chambers, Department of Transport, 136 Stirling Hwy, Nedlands,
West Australia 6007. Net: It is also
available by FTP from hiplab.newcastle.edu.au:/pub/Genie&Code.sea.Hqx
Genitor:
"Genitor is a modular GA package containing examples for floating-
point, integer, and binary representations. Its features include many
sequencing operators as well as subpopulation modeling.
The Genitor Package has code for several order based CROSSOVER
operators, as well as example code for doing some small TSPs to
optimality.
We are planning to release a new and improved Genitor Package this
summer (1993), but it will mainly be additions to the current package
that will include parallel island models, cellular GAs, delta coding,
perhaps CHC (depending on the legal issues) and some other things we
have found useful."
Genitor is available from Colorado State University Computer Science
Department by FTP from ftp.cs.colostate.edu:/pub/GENITOR.tar
Please direct all comments and questions to
. If these fail to work, contact: L.
Darrell Whitley, Dept. of Computer Science, Colorado State
University, Fort Collins, CO 80523, USA. Net:
(Unverified 8/94).
GENlib:
GENlib is a library of functions for GENETIC ALGORITHMs. Included
are two applications of this library to the field of neural networks.
The first one called "cosine" uses a genetic algorithm to train a
simple three layer feed-Forward network to work as a cosine-function.
This task is very difficult to train for a backprop algorithm while
the genetic algorithm produces good results. The second one called
"vartop" is developing a Neural Network to perform the XOR-function.
This is done with two genetic algorithms, the first one develops the
topology of the network, the second one adjusts the weights.
GENlib may be obtained by FTP from ftp.neuro.informatik.uni-
kassel.de:/pub/NeuralNets/GA-and-NN/
Author: Jochen Ruhland, FG Neuronale Netzwerke / Uni Kassel,
Heinrich-Plett-Str. 40, D-34132 Kassel, Germany.
GENOCOP:
This is a GA-based OPTIMIZATION package that has been developed by
Zbigniew Michalewicz and is described in detail in his book "Genetic
Algorithms + Data Structures = Evolution Programs" (Springer Verlag,
2nd ed, 1994).
GENOCOP (Genetic Algorithm for Numerical Optimization for COnstrained
Problems) optimizes a function with any number of linear constraints
(equalities and inequalities).
The second version of the system is available by FTP from
unccsun.uncc.edu:/coe/evol/genocop2.tar.Z
Zbigniew Michalewicz, Dept. of Computer Science, University of North
Carolina, Chappel-Hill, NC, USA. Net:
GIGA:
GIGA is designed to propogate information through a POPULATION, using
CROSSOVER as its operator. A discussion of how it propogates BUILDING
BLOCKs, similar to those found in Royal Road functions by John
Holland, is given in the DECEPTION section of: "Genetic Invariance: A
New Paradigm for Genetic Algorithm Design." University of Alberta
Technical Report TR92-02, June 1992. See also: "GIGA Program
Description and Operation" University of Alberta Computing Science
Technical Report TR92-06, June 1992
These can be obtained, along with the program, by FTP from
ftp.cs.ualberta.ca:/pub/TechReports/ in the subdirectories TR92-02/
and TR92-06/ .
Also, the paper "Mutation-Crossover Isomorphisms and the Construction
of Discriminating Functions" gives a more in-depth look at the
behavior of GIGA. Its is available from
ftp.cs.ualberta.ca:/pub/joe/Preprints/xoveriso.ps.Z
Joe Culberson, Department of Computer Science, University of Alberta,
CA. Net:
LibGA:
LibGA is a library of routines written in C for developing GENETIC
ALGORITHMs. It is fairly simple to use, with many knobs to turn.
Most GA parameters can be set or changed via a configuration file,
with no need to recompile. (E.g., operators, pool size and even the
data type used in the CHROMOSOME can be changed in the configuration
file.) Function pointers are used for the GENETIC OPERATORs, so they
can easily be manipulated on the fly. Several genetic operators are
supplied and it is easy to add more. LibGA runs on many
systems/architectures. These include Unix, DOS, NeXT, and Amiga.
LibGA Version 1.00 is available by FTP from
ftp.aic.nrl.navy.mil:/pub/galist/src/ga/libga100.tar.Z or by email
request to its author, Art Corcoran
(Unverified 8/94).
LICE:
LICE is a parameter OPTIMIZATION program based on EVOLUTION
STRATEGIEs (ES). In contrast to classic ES, LICE has a local
SELECTION scheme to prevent premature stagnation. Details and results
were presented at the EP'94 conference in San Diego. LICE is written
in ANSI-C (more or less), and has been tested on Sparc-stations and
Linux-PCs. If you want plots and graphics, you need X11 and gnuplot.
If you want a nice user interface to create parameter files, you also
need Tk/Tcl.
LICE-1.0 is available as source code by FTP from
lumpi.informatik.uni-dortmund.de:/pub/ES/src/LICE-1.0.tar.gz
Author: Joachim Sprave
mGA:
mGA is an implementation of a messy GA as described in TCGA report
No. 90004. Messy GAs overcome the linkage problem of simple GENETIC
ALGORITHMs by combining variable-length strings, GENE expression,
messy operators, and a nonhomogeneous phasing of evolutionary
processing. Results on a number of difficult deceptive test
functions have been encouraging with the messy GA always finding
global optima in a polynomial number of function evaluations.
See TCGA reports 89003, 90005, 90006, and 91004, and IlliGAL report
91008 for more information on messy GAs (See Q14). The C language
version is available by FTP from IlliGAL in the directory
gal4.ge.uiuc.edu:/pub/src/messyGA/C/
PARAGenesis:
PARAGenesis is the result of a project implementing Genesis on the
CM-200 in C*. It is an attempt to improve PERFORMANCE as much as
possible without changing the behavior of the GENETIC ALGORITHM.
Unlike the punctuated equilibria and local SELECTION models,
PARAGenesis doesn't modify the genetic algorithm to be more
parallelizable as these modifications can drastically alter the
behavior of the algorithm. Instead each member is placed on a
separate processor allowing initialization, evaluation and MUTATION
to be completely parallel. The costs of global control and
communication in selection and CROSSOVER are present but minimized as
much as possible. In general PARAGenesis on an 8k CM-200 seems to run
10-100 times faster than Genesis on a Sparc 2 and finds equivalent
solutions.
PARAGenesis includes all the features of serial Genesis plus some
additions. The additions include the ability to collect timing
STATISTICS, probabilistic SELECTION (as opposed to Baker's stochastic
universal sampling), uniform CROSSOVER and local or neighborhood
SELECTION. Anyone familiar with the serial implementation of Genesis
and C* should have little problem using PARAGenesis.
PARAGenesis is available by FTP from
ftp.aic.nrl.navy.mil:/pub/galist/src/ga/paragenesis.tar.Z
DISCLAIMER: PARAGenesis is fairly untested at this point and may
contain some bugs.
Michael van Lent, Advanced Technology Lab, University of Michigan,
1101 Beal Av., Ann Arbor, MI 48109, USA. Net:
.
PGA:
PGA is a simple testbed for basic explorations in GENETIC ALGORITHMs.
Command line arguments control a range of parameters, there are a
number of built-in problems for the GA to solve. The current set
includes:
o maximize the number of bits set in a CHROMOSOME
o De Jong's functions DJ1, DJ2, DJ3, DJ5
o binary F6, used by Schaffer et al
o a crude 1-d knapsack problem; you specify a target and a set of
numbers in an external file, GA tries to find a subset that sums
as closely as possible to the target
o the `royal road' function(s); a CHROMOSOME is regarded as a set of
consecutive blocks of size K, and scores K for each block entirely
filled with 1s, etc; a range of parameters.
o max contiguous bits, you choose the ALLELE range.
o timetabling, with various smart MUTATION options; capable of
solving a good many real-world timetabling problems (has done so)
Lots of GA options: rank, roulette, tournament, marriage-tournament,
spatially-structured SELECTION; one-point, two-point, uniform or no
CROSSOVER; fixed or adaptive MUTATION; one child or two; etc.
Default output is curses-based, with optional output to file; can be
run non-interactively too for batched series of experiments.
It's easy to add your own problems. CHROMOSOMEs are represented as
character arrays, so you are not (quite) stuck with bit-string
problem encodings.
PGA has been used for teaching for a couple of years now, and has
been used as a starting point by a fair number of people for their
own projects. So it's reasonably reliable. However, if you find bugs,
or have useful contributions to make, Tell Me! It is available by FTP
from ftp.dai.ed.ac.uk:pub/pga-2.7/pga-2.7.tar.Z (see the file
pga.README in the same directory for more information)
Peter Ross, Department of AI, University of Edinburgh, 80 South
Bridge, Edinburgh EH1 1HN, UK. Net:
SGA-C, SGA-Cube:
SGA-C is a C-language translation and extension of the original
Pascal SGA code presented in Goldberg's book [GOLD89]. It has some
additional features, but its operation is essentially the same as
that of the Pascal version. SGA-C is described in TCGA report No.
91002.
SGA-Cube is a C-language translation of Goldberg's SGA code with
modifications to allow execution on the nCUBE 2 Hypercube Parallel
Computer. When run on the nCUBE 2, SGA-Cube can take advantage of
the hypercube architecture, and is scalable to any hypercube
dimension. The hypercube implementation is modular, so that the
algorithm for exploiting parallel processors can be easily modified.
In addition to its parallel capabilities, SGA-Cube can be compiled on
various serial computers via compile-time options. In fact, when
compiled on a serial computer, SGA-Cube is essentially identical to
SGA-C. SGA-Cube is described in TCGA report No. 91005.
Each of these programs is distributed in the form of a Unix shar
file, available via e-mail or on various formatted media by request
from: Robert Elliott Smith, Department of Engineering of Mechanics,
Room 210 Hardaway Hall,, The University of Alabama P.O. Box 870278,
Tuscaloosa, Alabama 35487, USA. Net:
SGA-C and SGA-Cube are also available in compressed tar form by FTP
from ftp.aic.nrl.navy.mil:/pub/galist/src/ga/sga-c.tar.Z and sga-
cube.tar.Z .
Splicer:
Splicer is a GENETIC ALGORITHM tool created by the Software
Technology Branch (STB) of the Information Systems Directorate at
NASA/Johnson Space Center with support from the MITRE Corporation.
Splicer has well-defined interfaces between a GA kernel,
representation libraries, FITNESS modules, and user interface
libraries.
The representation libraries contain functions for defining,
creating, and decoding genetic strings, as well as multiple CROSSOVER
and MUTATION operators. Libraries supporting binary strings and
permutations are provided, others can be created by the user.
FITNESS modules are typically written by the user, although some
sample applications are provided. The modules may contain a fitness
function, initial values for various control parameters, and a
function which graphically displays the best solutions.
Splicer provides event-driven graphic user interface libraries for
the Macintosh and the X11 window system (using the HP widget set); a
menu-driven ASCII interface is also available though not fully
supported. The extensive documentation includes a reference manual
and a user's manual; an architecture manual and the advanced
programmer's manual are currently being written.
An electronic bulletin board (300/1200/2400 baud, 8N1) with
information regarding Splicer can be reached at (713) 280-3896 or
(713) 280-3892. Splicer is available free to NASA and its
contractors for use on government projects by calling the STB Help
Desk weekdays 9am-4pm CST at (713) 280-2233. Government contractors
should have their contract monitor call the STB Help Desk; others may
purchase Splicer for $221 (incl. documentation) from: COSMIC, 382 E.
Broad St., Athens, GA 30602, USA. (Unverified 8/94). Last known
address (Steve Bayer). This now bounces
back with "user unknown".
TOLKIEN:
TOLKIEN (TOoLKIt for gENetics-based applications) is a C++ class
library, intended for those involved in GAs and CLASSIFIER SYSTEM
research with a working knowledge of C++. It is designed to reduce
effort in developing genetics-based applications by providing a
collection of reusable objects. For portability, no compiler
specific or class library specific features are used. The current
version has been compiled successfully using Borland C++ Version 3.1
and GNU C++.
TOLKIEN contains a lot of useful extensions to the generic GENETIC
ALGORITHM and CLASSIFIER SYSTEM architecture. Examples include: (i)
CHROMOSOMEs of user-definable types; binary, character, integer and
floating point; (ii) Gray code encoding and decoding; (iii) multi-
point and uniform CROSSOVER; (iv) diploidy and dominance; (v) various
SELECTION schemes such as tournament selection and linear ranking;
(vi) linear FITNESS scaling and sigma truncation; (vii) the simplest
one-taxon-one-action classifiers and the general two-taxa-one-action
classifiers.
TOLKIEN is available from ENCORE (See Q15.3) in file:
GA/src/TOLKIEN.tar.gz The documentation and two primers on how to
build GA and CFS applications alone are available as:
GA/docs/tolkien-doc.tar.gz
Author: Anthony Yiu-Cheung Tang , Department of
Computer Science (Rm 913), The Chinese University of Hong Kong. Tel:
609-8403, 609-8404.
WOLF:
This is a simulator for the G/SPLINES (genetic spline models)
algorithm which builds spline-based functional models of experimental
data, using CROSSOVER and MUTATION to evolve a POPULATION towards a
better fit. It is derived from Friedman's MARS models. The original
work was presented at ICGA-4, and further results including
additional basis function types such as B-splines have been presented
at the NIPS-91 meeting.
Available free by FTP by contacting the author; runs on SUN (and
possibly any SYSV) UNIX box. Can be redistributed for noncommercial
use. Simulator includes executable and C source code; a technical
report (RIACS tech report 91.10) is also available.
David Rogers, MS Ellis, NASA Ames Research Center, Moffett Field, CA
94035, USA. Net:
CLASSIFIER SYSTEMS
CFS-C:
CFS-C 1.0 is a domain independent collection of CLASSIFIER SYSTEM
routines written by Rick L. Riolo as part of his PhD dissertation. A
completely rewritten CFS-C is planned for 1994/95; this may include
the features of CFS-C 2.0 mentioned in [SAB90] (e.g. "latent
learning") or they may be included in a separate package released in
1995. An ANSIfied version of CFS-C 1.0 (CFS-C 1.98j) is available by
FTP.
CFS-C is available from ENCORE (See Q15.3) in file:
CFS/src/cfsc-1.98j.tar.gz and includes the original 1.02 CFS-C in
it's "cfsc/orig" folder after unpacking. On the "SyS" FTP server
it's: lumpi.informatik.uni-dortmund.de:/pub/LCS/src/cfsc-1.98j.tar.gz
with documentation in /pub/LCS/docs/cfsc.ps.gz
Another version of CFS-C (version XV 0.1) by Jens Engel
is also available. This includes
bug fixes of earlier versions, allowing it to run on a wider range of
machines (e.g. Linux and nCUBE). It also has an XView front end that
makes it easier to control, and some extensions to the algorithms.
It is available from ENCORE in file: CFS/src/cfscxv-0.1.tar.gz with
documentation in CFS/docs/cfscxv-0.1.readme.gz
References
Rick L. Riolo (1988) "CFS-C: A package of domain independent
subroutines for implementing classifier systems in arbitrary, user-
defined environments", Logic of computers group, Division of computer
science and engineering, University of Michigan.
Rick L. Riolo (1988) "LETSEQ: An implementation of the CFS-C
classifier-system in a task-domain that involves learning to predict
letter sequences", Logic of computers group, Division of computer
science and engineering, University of Michigan.
Rick L. Riolo (1988) "CFS-C/FSW1: An implementation of the CFS-C
classifier system in a task domain that involves learning to traverse
a finite state world", Logic of computers group, Division of computer
science and engineering, University of Michigan.
SCS-C:
SCS-C is a (`mostly ANSI') C language translation and extension of
Goldberg's Simple CLASSIFIER SYSTEM, as presented in Appendix D in
his seminal book [GOLD89].
SCS-C has been developed in parallel on a Sun 10/40 and an ATARI ST,
and thus should be quite portable; it's distributed free of charge
under the terms of the GNU General Public License. Included are some
additional goodies, e.g. the VAX/VMS version of SCS, rewritten in C
by Erik Mayer .
SCS-C v1.0j is available from ENCORE (See Q15.3), by FTP in file
EC/CFS/src/scsc-1.0j.tar.gz
For more information contact: Joerg Heitkoetter, EUnet Deutschland
GmbH, Techo-Park, Emil-Figge-Str. 80, D-44227 Dortmund, Germany.
Net: .
------------------------------
Subject: Q20.2: Commercial software packages?
EnGENEer:
Logica Cambridge Ltd. developed EnGENEer as an in-house GENETIC
ALGORITHM environment to assist the development of GA applications on
a wide range of domains. The software was written in C and runs under
Unix as part of a consultancy and systems package. It supports both
interactive (X-Windows) and batch (command-line) modes of operation.
EnGENEer provides a number of flexible mechanisms which allow the
developer to rapidly bring the power of GAs to bear on new problem
domains. Starting with the Genetic Description Language, the
developer can describe, at high level, the structure of the ``genetic
material'' used. The language supports discrete GENEs with user
defined cardinality and includes features such as multiple
CHROMOSOMEs models, multiple SPECIES models and non-evolvable parsing
symbols which can be used for decoding complex genetic material.
The user also has available a descriptive high level language, the
Evolutionary Model Language. It allows the description of the GA type
used in terms of configurable options including: POPULATION size,
population structure and source, SELECTION method, CROSSOVER and
MUTATION type and probability, INVERSION, dispersal method, and
number of OFFSPRING per GENERATION.
Both the Genetic Description Language and the Evolutionary Model
Language are fully supported within the interactive interface
(including online help system) and can be defined either "on the fly"
or loaded from audit files which are automatically created during a
GA run.
Monitoring of GA progress is provided via both graphical tools and
automatic storage of results (at user defined intervals). This allows
the user to restart EnGENEer from any point in a run, by loading both
the POPULATION at that time and the evolutionary model that was being
used.
Connecting EnGENEer to different problem domains is achieved by
specifying the name of the program used to evaluate the problem
specific FITNESS function and constructing a simple parsing routine
to interpret the genetic material. A library of standard
interpretation routines are also provided for commonly used
representation schemes such as gray-coding, permutations, etc. The
fitness evaluation can then be run as either a slave process to the
GA or via a standard handshaking routines. Better still, it can be
run on either the machine hosting the EnGENEer or on any sequential
or parallel hardware capable of connecting to a Unix machine.
For more information, contact: George Robbins, Systems Intelligence
Division, Logica Cambridge Ltd., Betjeman House, 104 Hills Road,
Cambridge CB2 1LQ, UK. Tel: +44 716 379111, Fax: +44 223 322315
(Unverified 8/94).
EvoFrame:
EvoFrame is to EVOLUTION STRATEGIEs what MicroGA is to GENETIC
ALGORITHMs, a toolkit for application development incorporating ESs
as the OPTIMIZATION engine.
EvoFrame is an object oriented implemented programming tool for
EVOLUTION STRATEGIEs (Rechenberg/Schwefel, Germany) for easy
implementation and solution of numerical and combinatorical problems.
EvoFrame gives you freedom of implementing every byte of the
OPTIMIZATION principle and its user interface. You can focus on the
optimization problem and forget about all the rest.
EvoFrame is available as Version 2.0 in Borland-Pascal 7.0 and Turbo-
Vision for PC's and as Version 1.0 in C++ for Apple Macintosh using
MPW and MacApp. Both implementations allow full typed
implementation, i.e. no more translation from problem specific
format to an OPTIMIZATION specific one. A prototyping tool (cf
REALizer) exists for both platforms too.
EvoFrame allows pseudoparallel OPTIMIZATION of many problems at once
and you can switch optimization parameters and internal methods (i.e.
quality function etc.) during runtime and during optimization cycle.
Both tools can be modified or extended by overloading existing
methods for experimental use. They are developed continously in
correlation to new research results.
The PC version is prepared for experimental use due to a
comprehensive protocolling mechanism of optimzation cycles and user
data. It also allows compilation of executable files with different
complexity by setting conditional compilation flags. It can be used
with 3 levels of stacked POPULATIONs.
The Mac version is the more complex (recursive) implementation. It
allows stacking of any number of POPULATIONs for modelling of complex
systems. Theory stops at multipopulation level at the time. EvoFrame
for Mac is ready for the future, allowing any number of population
levels.
Ask for porting the Mac version (C++) to any other platform, i.e. X
Windows.
REALizer is a tool for rapid prototyping of EvoFrame applications.
It's an override of the corresponding framework which is prepared to
optimize using a vector of real numbers. All methods for standard
EVOLUTION and file handling, etc. are ready implemented. The
remaining work for the user is to define a constant for the problem
size, fill in the quality function and start the OPTIMIZATION
process.
For further information, current prices and orders, contact: Wolfram
Stebel, Optimum Software, Braunfelser Str. 26, 35578 Wetzlar,
Germany. Net:
Evolver:
Evolver is a spreadsheet add-in which incorporates "the first
commercially available GENETIC ALGORITHM to search for solutions".
Evolver can be customized through a macro language, and is available
for $345 on 3.5'' or 5.25'' floppies for the Excel, WingZ and Resolve
spreadsheets on the Mac and PC computers. For further information,
contact: Axcelis, Inc., 4668 Eastern Avenue North, Seattle, WA
98103-6932, USA. Tel: (206) 632-0885.
To order Evolver, contact: Spreadware Distributors, P.O. Box 4552,
Palm Desert, CA 92261, USA. Tel: (619) 347-2365, Fax: (619) 347-6045
(Unverified 8/94).
GAME:
GAME (GA Manipulation Environment) aims to demonstrate GA
applications and build a suitable programming ENVIRONMENT.
GAME is being developed as part of the PAPAGENA project of the
European Community's Esprit III initiative.
GAME is available as an addendum to a book on PGAs (cf PAPAGENA,
Q20.3). And from the project's FTP server
bells.cs.ucl.ac.uk:/papagena/ e.g. "papagena/game/docs" contains all
the papers that have been produced over the course of the GAME
project, e.g. you'll find a little bit outdated draft of the GAME
DESIGN NOTES document, which explains some of the details of the
implementation. There are some other technical reports also. The
sources can also be obtained by FTP see papagena/game/version2.01/
GAME is now in version 2.01 (the version distributed with the book
was 1.0). This version is still able to run only sequential GAs, but
version 3.0 is coming soon and will handle parallel GAs as well.
Unfortunately, The project yet only produced a Borland C++ 3.x
version, so far. It is intended to distribute a version for UNIX/GNU
C++ as well, when some compatibility issues concerning C++
"standards" have been resolved. Afterward a UNIX version will be
released, but this will be only happen after the release of PC
version 3.0.
Please, feel free to use and distribute the software.
For more information contact: Jose Luiz Ribeiro Filho, Department of
Computer Science, University College London, Gower Street, London
WC1E 6BT, UK. Net: (Unverified 8/94).
MicroGA:
MicroGA is a powerful and flexible new tool which allows programmers
to integrate GAs into their software quickly and easily. It is an
object-oriented C++ framework that comes with full source code and
documentation as well as three sample applications. Also included is
the Galapagos code generator which allows users to create complete
applications interactively without writing any C++ code, and a sample
MacApp interface.
MicroGA is available for Macintosh II or higher with MPW and a C++
compiler, and also in a Microsoft Windows version for PC compatibles.
Compiled applications made with MicroGA can be sold without license
fee. MicroGA is priced at $249.
Galapagos is a tool for use with Emergent Behavior's MicroGA Toolkit.
It allows a user to define a function and set of constraints for a
problem that the user wants to solve using the GA. Galapagos then
generates a complete C++ program using the information supplied. Then
all the user has to do is to compile these files, using either
Turbo/Borland C++ (PC, MS Windows), or MPW and C++ compiler
(Macintosh), and link the resulting code to the MicroGA library. Then
just run the program. Galapagos comes free with every copy of
MicroGA.
For further information and orders, contact: Steve Wilson, Emergent
Behavior, 635 Wellsbury Way, Palo Alto, CA 94306, USA. Net:
MicroGA is distributed in Germany by Optimum Software (cf EvoFrame &
REALizer entries).
Omega:
The Omega Predictive Modeling System, marketed by KiQ Limited, is a
powerful approach to developing predictive models. It exploits
advanced GA techniques to create a tool which is "flexible, powerful,
informative and straightforward to use". Omega is geared to the
financial domain, with applications in Direct Marketing, Insurance,
Investigations and Credit Management. The ENVIRONMENT offers
facilities for automatic handling of data; business, statistical or
custom measures of PERFORMANCE, simple and complex profit modeling,
validation sample tests, advanced confidence tests, real time
graphics, and optional control over the internal GA.
For further information, contact: KiQ, Business Modeling Systems
Ltd., Easton Hall, Great Easton, Essex CM6 2HD, UK. Tel: +44 371
870254 (Unverified 8/94).
OOGA:
OOGA (Object-Oriented GA) is a GENETIC ALGORITHM designed for
industrial use. It includes examples accompanying the tutorial in
the companion "Handbook of Genetic Algorithms". OOGA is designed such
that each of the techniques employed by a GA is an object that may be
modified, displayed or replaced in object-oriented fashion. OOGA is
especially well-suited for individuals wishing to modify the basic GA
techniques or tailor them to new domains.
The buyer of OOGA also receives Genesis (see above). This release
sports an improved user interface. OOGA and Genesis are available
together on 3.5'' or 5.25'' disk for $60 ($52.50 inside North
America) by order from: The Software Partnership (T.S.P.), P.O. Box
991, Melrose, MA 02176, USA. Tel: +1 617 662 8991 (Unverified 8/94).
PC-Beagle:
PC-Beagle is a rule-finder program for PCs which examines a database
of examples and uses machine-learning techniques to create a set of
decision rules for classifying those examples, thus turning data into
knowledge. The system contains six major components, one of which
(HERB - the "Heuristic Evolutionary Rule Breeder") uses GA techniques
to generate rules by natural SELECTION.
PC-Beagle is available to educational users for 69 pounds sterling.
Orders, payment or requests for information should be addressed to:
Richard Forsyth, Pathway Research Ltd., 59 Cranbrook Rd., Bristol BS6
7BS, UK. Tel: +44 272 428692 (Unverified 8/94).
XpertRule GenAsys:
XpertRule GenAsys is an expert system shell with embedded GENETIC
ALGORITHM marketed by Attar Software. Targeted to solve scheduling
and design applications, this system combines the power of genetic
algorithms in evolving solutions with the power of rule-based
programming in analyzing the effectiveness of solutions. Rule-based
programming can also be used to generate the initial POPULATION for
the genetic algorithm and for post-optimization planning. Some
examples of design and scheduling problems which can be solved by
this system include: OPTIMIZATION of design parameters in electronic
and avionic industries, route optimization in the distribution
sector, production scheduling in manufacturing, etc.
For further information, contact: Attar Software, Newlands Road,
Leigh, Lancashire, UK. Tel: +44 942 608844. (Unverified 8/94).
Last known address <100166.1547@CompuServe.com>. This now bounces
back with "user unknown".
XYpe:
XYpe (The GA Engine) is a commercial GA application and development
package for the Apple Macintosh. Its standard user interface allows
you to design CHROMOSOMEs, set attributes of the genetic engine and
graphically display its progress. The development package provides a
set of Think C libraries and include files for the design of new GA
applications. XYpe supports adaptive operator weights and mixtures of
alpha, binary, gray, ordering and real number codings.
The price of $725 (in Massachusetts add 5% sales tax) plus $15
shipping and handling includes technical support and three
documentation manuals. XYpe requires a Macintosh SE or newer with
2MB RAM running OS V6.0.4 or greater, and Think C if using the
development package.
Currently the GA engine is working; the user interface will be
completed on demand. Interested parties should contact: Ed Swartz,
Virtual Image, Inc., 75 Sandy Pond Road #11, Ayer, MA 01432, USA.
Tel: +1 (508) 772-4225 (Unverified 8/94).
------------------------------
Subject: Q20.3: Current research projects?
PAPAGENA:
The European ESPRIT III project PAPAGENA is pleased to announce the
availability of the following book and software:
Parallel Genetic Algorithms: Theory and Applications was recently
published by IOS press. The book, edited by Joachim Stender, provides
an overview of the theoretical, as well as practical, aspects
involved in the study and implementation of parallel GENETIC
ALGORITHMs (PGAs).
The book comes with a floppy disk version of GAME (Genetic Algorithm
Manipulation Environment). For more information see the section on
GAME in Q20.2.
PeGAsuS:
PeGAsuS is a general programming environment for evolutionary
algorithms. developed at the German National Research Center for
Computer Science. Written in ANSI-C, it runs on MIMD parallel
machines, such as transputers, and distributed systems, as well as
serial machines.
The Library contains GENETIC OPERATORs, a collection of FITNESS
functions, and input/output and control procedures. It provides the
user with a number of validated modules. Currently, PeGAsuS can be
compiled with the GNU C, RS/6000 C, ACE-C, and Alliant's FX/2800 C
compilers. It runs on SUNs and RS/6000 workstations, as well as on
the Alliant FX/28. PeGAsuS is not available to the public.
For more information contact: Dirk Schlierkamp-Voosen, Research Group
for Adative Systems, German National Research Center for Computer
Science, 53731 Sankt Augustin, Germany. Net:
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End of ai-faq/genetic/part5
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