FYI:GP-97 Revised Call for Participation (fwd)

Eugene Leitl (
Sun, 11 May 1997 09:41:11 +0200 (MET DST)

---------- Forwarded message ----------
Date: Sat, 10 May 1997 13:09:18 -0700 (PDT)
From: John R. Koza <koza@CS.Stanford.EDU>
To: cellular-automata@BUPHY.BU.EDU
Subject: GP-97 Revised Call for Participation


Genetic Programming 1997 Conference (GP-97)
July 13 - 16 (Sunday - Wednesday), 1997
Fairchild Auditorium - Stanford University - Stanford, California
In cooperation with American Association for Artificial Intelligence (AAAI),
Association for Computing Machinery (ACM), SIGART, and Society for Industrial
and Applied Mathematics (SIAM)
NOTE: You are urged to make your housing arrangements as early as possible
since convenient hotel locations are limited. Also, if you are driving
to the Stanford campus, please be aware of parking lot construction in
the area of Fairchild Auditorium and allow a little extra time
(particularly on the first Monday session) to find a parking place.
Genetic programming is an automatic programming technique for evolving
computer programs that solve (or approximately solve) problems. Starting with
a primordial ooze of thousands of randomly created computer programs, a
population of programs is progressively evolved over many generations using
the Darwinian principle of survival of the fittest, a sexual recombination
operation, and occasional mutation.

The first annual genetic programming conference in 1996 featured 15 tutorials,
2 invited speakers, 3 parallel tracks, 73 papers, and 17 poster papers in
proceedings book, and 27 late-breaking papers in a separate book distributed
to conference attendees, and 288 attendees. A description of GP-96 appears in
the October 1996 issue of Scientific American
( This second annual
conference in 1997 reflects the rapid growth of this field in which over 600
technical papers have been published since 1992. For August 5, 1996 article
in E. E. Times on GP-96 conference and August 12, 1996 article in E. E Times
on John Holland's invited speech at GP-96, go to

There will be 36 long, 33 short, and 15 poster papers at the Second Annual
Genetic Programming Conference to be held on July
13-16 (Sunday - Wednesday), 1997 at Stanford University.
In addition, there will be late-breaking papers (published in a separate
book in mid June after the June 11 deadline for late-breaking papers).
Topics include, but are not limited to,
applications of genetic programming, theoretical foundations of
genetic programming, implementation issues, technique extensions, cellular
encoding, evolvable hardware, evolvable machine language programs, automated
evolution of program architecture, evolution and use of mental models,
automatic programming of multi-agent strategies, distributed artificial
intelligence, auto-parallelization of algorithms, automated circuit synthesis,
automatic programming of cellular automata, induction, system identification,
control, automated design, data and image compression, image analysis, pattern
recognition, molecular biology applications, grammar induction, and
parallelization. Papers describing recent developments are also solicited in
the following additional areas: genetic algorithms, classifier systems,
evolutionary programming and evolution strategies, artificial life and
evolutionary robotics, DNA computing, and evolvable hardware.


- Ellen Goldberg, President, Santa Fe Institute
- Susumu Ohno, Ben Horowitz Chair of Distinguished Scientist in Theoretical
Biology, Beckman Research Institute
- David B. Fogel, Natural Selection Inc. and Editor-In-Chief of the
IEEE Transactions on Evolutionary Computation


The main focus of the conference (and most of the papers) will be on genetic
programming. In addition, papers describing recent developments in the
closely related areas will be reviewed and selected by special program
committees appointed and supervised by the following special program chairs.

--- Genetic Algorithms: Kalyanmoy Deb, Indian Inst of Tech - Kanpur, India

--- Classifier Systems: Rick L. Riolo, University of Michigan

--- Evolutionary Programming and Evolution Strategies: David B. Fogel,
Natural Selection Inc, San Diego

--- Artificial Life and Evolutionary Robotics: Marco Dorigo, Universite
Libre de Bruxelles

--- DNA Computing: Max Garzon, University of Memphis

--- Evolvable Hardware: Hitoshi Iba, Electrotechnical Laboratory, Japan

20 TUTORIALS AT GP-97 (Note: Slight Revisions from earlier listing)

Sunday July 13 - 9:15 AM - 11:30 AM
--- Genetic Algorithms - David E. Goldberg, University of Illinois at Urbana-
--- Evolvable Hardware - Tetsuya Higuchi - Electrotechnical Laboratory,
Tsukuba, Japan
--- Program Growth Control in Genetic Programming - Byoung-Tak Zhang, Konkuk
University, Seoul, South Korea and Hitoshi Iba, Electrotechnical Laboratory,
Tsukuba, Japan
--- Introduction to Genetic Programming - John Koza, Stanford University
Sunday July 13 - 1:00 PM - 3: 15 PM
--- Evolutionary Algorithms for Computer-Aided Design of Integrated Circuits -
Rolf Drechsler - Albert-Ludwigs-University, Freiburg, Germany
--- Self-Replicating Systems in Cellular Space Models - Jason Lohn - Stnaofrd University
--- Neural Networks - Bernard Widrow - Stanford University
--- Advanced Genetic Programming - John Koza, Stanford University
Sunday July 13 - 3:45 PM - 6 PM
--- Evolutionary Programming and Evolution Strategies - David Fogel,
University of California, San Diego
--- Genetic Programming Representations - Astro Teller - Carnegie Mellon
--- Design of Electrical Circuits using Genetic Programming - David Andre
University of California - Berkeley and Forrest H Bennett III - Stanford
--- Genetic Programming with Linear Genomes - Wolfgang Banzhaf, University of
Dortmund, Germany
Tuesday July 15 - 3:25 PM - 5:40 PM
--- Computational Learning Theory - Vasant Honavar - Iowa State University
--- Machine Learning - Pat Langley, Institute for the Study of Learning and
--- Molecular Biology for Computer Scientists - Russ B. Altman, Stanford
--- Simulated Evolution of Models - Janine Graf - Inquire America Corp
Tuesday July 15 - 7:30 PM - 9:30 PM
--- DNA Computing - Russell Deaton and Randy C. Murphy - University of Memphis
--- Evolutionary Algorithms with Mathematica - Christian Jacobs
--- Cellular Programming: Evolution Of Parallel Cellular Machines - Moshe
Sipper - Swiss Federal Institute of Technology, Lausanne
--- Machine Language Genetic Programming - Peter Nordin
DaCapo AB, Sweden
GENERAL CHAIR: John Koza, Stanford University
PUBLICITY CHAIR: Patrick Tufts, Brandeis University
EXECUTIVE COMMITTEE: David Andre, Forrest H Bennett III, Jason Lohn
the World Wide Web: E-
MAIL: PHONE: 415-328-3123. FAX: 415-321-4457. The conference
is operated by Genetic Programming Conferences, Inc. (a California not-for-
profit corporation).
Hotel information: Numerous local hotels within a short distance of Stanford
University are listed at the GP-97 home page. Because of other events held in
the area during the summer, attendees are urged to make their arrangements for
accomodations early. For your convenience, AAAI has reserved a block of rooms
at the Holiday Inn-Palo Alto Hotel, 625 El Camino Real, Palo Alto, CA 94301,
Phone: 800-874-3516 or 415-328-2800, FAX: 415-327-7362. Make your
reservations directly with the Holiday Inn before June 28, 1997 for the GP-97
rate rate of $99 single and $109 double. In addition, AAAI has reserved a
block of rooms at the Stanford Terrace Inn, 531 Stanford Avenue, Palo Alto, CA
94306, Phone: 800-729-0332 or 415-857-0333, FAX: 415-857-0343. Make your
reservations directly with the Stanford Terrace Inn before June 11, 1997.
There is a free Stanford University shuttle (called Marguerite) that stops
near both of these hotels (and various other hotels, the train station, and
Palo Alto locations).
University Housing information: A limited number of spaces are available at
Stanford University housing on a first-come-first-served basis. The final
deadline for University housing applications is June 13, 1997. See the GP-97
WWW home page for a university housing application form.
TRAVEL INFORMATION: Stanford University is near Palo Alto in Northern
California and is about 40 miles south of San Francisco. Stanford is about 25
miles south of the San Francisco International Airport and about 25 miles
north of San Jose International Airport. Oakland airport is about 45 miles
away. Conventions in America has arranged special GP-97 airline and car
rental discounts. For travel between July 10 - 20, 1997, American Airlines
can save you 5% on lowest applicable fares or 10% off lowest unrestricted
coach fares, with 7-day advance purchases. Some restrictions apply. Hertz is
offering special low conference rates with unlimited free mileage. Please
contact Conventions in America concerning "Group #428" at 1-800-929-4242; or
phone 619-678-3600; or FAX 619-678-3699 or e-mail you
call American Airlines direct at 800-433-1790, ask for "Index #S9485." If you
call Hertz direct at 800-654-2240, ask for "CV #24250." See the GP-97 WWW
home page for additional details.
University home page at, the Hyperion Guide at; the Palo Alto weekly at; the California Virtual Tourist at; and the
Yahoo Guide of San Francisco at
with the 45th Anniversary meeting of the Society for Industrial and Applied
Mathematics (SIAM) on July 14-18, 1997 at Stanford University
( GP-97 comes just after the IEEE International
Symposium on Computational Intelligence in Robotics and Automation (CIRA-97)
on July 10 - 11, 1997 in Monterey, California (90 miles from Stanford
University) and the IEEE 8th International Conference on Advanced Robotics
(ICAR-97) on July 5 - 9, 1997 in Monterey Other
non-California conferences of interest include AAAI-97 on July 27-31, 1997 in
Providence, Rhode Island (; ICGA-97 on July 20-23, 1997
in East Lansing, Michigan (; European
Artificial Life Conference on July 28-31, 1997 in Brighton, England
(; and IJCAI-97 on August 26-29, 1997 in
Nagoya, Japan (
MEMBERSHIP IN THE ACM, AAAI, or SIAM: For information about ACM membership,
go to; for SIGART,; for AAAI; and for SIAM, There is a discount
on GP-97 registration fees for members of ACM, SIGART, AAAI, and SIAM.
ADDRESSES FOR GP-97: GP-97 Conference, c/o American Association for
Artificial Intelligence, 445 Burgess Drive, Menlo Park, CA 94025. PHONE: 415-
328-3123. FAX: 415-321-4457. E-MAIL: WWW FOR AAAI: WWW FOR GP-97: http://www-cs-


July 13 - 16 (Sunday - Wednesday), 1997 at Stanford University
First Name ________________ Last Name _____________
Affiliation _________________________________________
Address ____________________________________________
City _______________________ State/Province _________
Zip/Postal Code ______________ Country _______________
Daytime telephone __________________________________
E-Mail address _____________________________________

Conference registration fee includes admission to all conference sessions and
events, one copy of conference proceedings book, attendance at 5 tutorials of
your choice, syllabus books for your 5 tutorials, Sunday night welcoming wine
and cheese reception, Monday night conference dinner reception, one copy of a
book of late-breaking papers, the conference T-shirt, 4 box lunches, and
coffee breaks.

Conference proceedings will be mailed to registered attendees with U.S.
mailing addresses via 2-day U.S. priority mail about 1 - 2 weeks prior to the
conference at no extra charge (at addressee's risk). If you are uncertain as
to whether you will be at the above address at that time or DO NOT WANT your
proceedings mailed to you at the above address for any other reason, your copy
of the proceedings will be held for you at the conference registration desk if
you check here ___.
Postmarked by June 19
Student - ACM, SIAM or AAAI Member - $245
Regular - ACM, SIAM, or AAAI Member - $445
Student - Non-member - $265
Regular - Non-member - $465
Postmarked after June 19, 1997 or on-site - Add $50 to June 19 rates
Member Number:
ACM # ___________ SIAM # _________ AAAI # _________
Students must send legible proof of full-time student status.
Stanford Parking Permits ($6 per day - C). Number of days ___ Total $_____
Grand Total (enter appropriate amount) $ _____________
___ Check or money order made payable to "AAAI" (in U.S. funds)
___ Mastercard ___ Visa ___ American Express
Credit card number __________________________________________
Expiration Date _________
Signature ____________________________________________
T-Shirt Size: ___ small ___ medium ___ large ___ extra-large
TUTORIALS: Check off a box for one tutorial from each of the 6 rows:
Sunday July 13 - 9:15 AM - 11:30 AM
--- Genetic Algorithms
--- Evolvable Hardware
--- Program Growth Control in Genetic Programming
--- Introduction to Genetic Programming
Sunday July 13 - 1:00 PM - 3: 15 PM
--- Evolutionary Algorithms for Computer-Aided Design of Integrated Circuits
--- Self-Replicating Systems in Cellular Space Models
--- Neural Networks
--- Advanced Genetic Programming
--- Evolutionary Programming and Evolution Strategies
--- Genetic Programming Representations
--- Design of Electrical Circuits using Genetic Programming
--- Genetic Programming with Linear Genomes
Tuesday July 15 - 3:25 PM - 5:40 PM
--- Computational Learning Theory
--- Simulated Evolution of Models
--- Machine Learning
--- Molecular Biology for Computer Scientists
Tuesday July 15 - 7:30 PM - 9:30 PM
--- DNA Computing
--- Evolutionary Algorithms with Mathematica
--- Cellular Programming: Evolution Of Parallel Cellular Machines
--- Machine Language Genetic Programming
No refunds will be made; however, we will transfer your registration to a
person you designate upon notification.
SEND TO: GP-97 Conference, c/o American Association for Artificial
Intelligence, 445 Burgess Drive, Menlo Park, CA 94025. PHONE: 415-328-3123.
FAX: 415-321-4457. E-MAIL: WWW FOR AAAI:


List of 84 Papers for Second Annual Genetic Programming
Conference (GP-97), July 13-16, 1997, Stanford University


Ahluwalia, Manu, Larry Bell, and Terence C. Fogarty
Co-evolving Functions in Genetic Programming: A Comparison
in ADF Selection Strategies

Angeline, Peter J.
Subtree Crossover: Building Block Engine or Macromutation?

Ashlock, Dan
GP-Automata for Dividing the Dollar

Ashlock, Dan, and Charles Richter
The Effect of Splitting Populations on Bidding Strategies

Banzhaf, Wolfgang, Peter Nordin, and Markus Olmer
Generating Adaptive Behavior for a Real Robot using Function
Regression within Genetic Programming

Bennett III, Forrest H
A Multi-Skilled Robot that Recognizes and Responds to
Different Problem Environments

Bruce, Wilker Shane
The Lawnmower Problem Revisited: Stack-Based Genetic
Programming and Automatically Defined Functions

Chen, Shu-Heng, and Chia-Hsuan Yeh
Using Genetic Programming to Model Volatility in Financial
Time Series

Daida, Jason, Steven Ross, Jeffrey McClain, Derrick Ampy, and
Michael Holczer
Challenges with Verification, Repeatability, and Meaningful
Comparisons in Genetic Programming

Dain, Robert A.
Genetic Programming For Mobile Robot Wall-Following

Deakin, Anthony G., and Derek F. Yates
Economical Solutions with Genetic Programming: the Non-
Hamstrung Squadcar Problem, FvM and EHP

Dracopoulos, Dimitris C.
Evolutionary Control of a Satellite

Droste, Stefan
Efficient Genetic Programming for Finding Good Generalizing
Boolean Functions

Eberbach, Eugene
Enhancing Genetic Programming by $-calculus

Esparcia-Alcazar, Anna J., and Ken Sharman
Evolving Recurrent Neural Network Architectures by Genetic

Fernandez, Thomas, and Matthew Evett
Training Period Size and Evolved Trading Systems

Freitas, Alex A.
A Genetic Programming Framework for Two Data Mining
Tasks: Classification and Generalized Rule Induction

Fuchs, Matthias, Dirk Fuchs, and Marc Fuchs
Solving Problems of Combinatory Logic with Genetic

Gathercole, Chris, and Peter Ross
Small Populations over Many Generations can beat Large
Populations over Few Generations in Genetic Programming

Gathercole, Chris, and Peter Ross
Tackling the Boolean Even N Parity Problem with Genetic
Programming and Limited-Error Fitness

Geyer-Schulz, Andreas
The Next 700 Programming Languages for Genetic

Gray, H. F., and R. J. Maxwell
Genetic Programming for Multi-class Classification of Magnetic
Resonance Spectroscopy Data

Greeff, D. J., and C. Aldrich
Evolution of Empirical Models for Metallurgical Process

Gritz, Larry, and James K. Hahn
Genetic Programming Evolution of Controllers for 3-D
Character Animation

Harries, Kim, and Peter Smith
Exploring Alternative Operators and Search Strategies in
Genetic Programming

Haynes, Thomas
On-line Adaptation of Search via Knowledge Reuse

Haynes, Thomas, and Sandip Sen
Crossover Operators for Evolving A Team

Hiden, Hugo, Mark Willis, Ben McKay, and Gary Montague
Non-Linear And Direction Dependent Dynamic Modelling
Using Genetic Programming

Hooper, Dale C., Nicholas S. Flann, and Stephanie R. Fuller
Recombinative Hill-Climbing: A Stronger Search Method for
Genetic Programming

Howley, Brian
Genetic Programming and Parametric Sensitivity: a Case Study
In Dynamic Control of a Two Link Manipulator

Huelsbergen, Lorenz
Learning Recursive Sequences via Evolution of Machine-
Language Programs

Iba, Hitoshi
Multiple-Agent Learning for a Robot Navigation Task by
Genetic Programming

Jaske, Harri
On code reuse in genetic programming

Koza, John R., Forest H. Bennett III, Martin A. Keane,
and David Andre
Evolution of a Time-Optimal Fly-To Controller Circuit using
Genetic Programming

Koza, John R., Forest Bennett III, Jason Lohn, Frank Dunlap,
Martin A. Keane, and David Andre
Use of Architecture-Altering Operations to Dynamically Adapt a
Three-Way Analog Source Identification Circuit to
Accommodate a New Source

Langdon, W. B., and R. Poli
An Analysis of the MAX Problem in Genetic Programming

Lensberg, Terje
A Genetic Programming Experiment on Investment Behavior
under Knightian Uncertainty

Luke, Sean, and Lee Spector
A Comparison of Crossover and Mutation in Genetic

Moore, Frank W., and Dr. Oscar N. Garcia
A Genetic Programming Approach to Strategy Optimization in
the Extended Two-Dimensional Pursuer/Evader Problem

Nordin, Peter, and Wolfgang Banzhaf
Genetic Reasoning Evolving Proofs with Genetic Search

Park, YoungJa, and ManSuk Song
Genetic Programming Approach to Sense Clustering in Natural
Language Processing

Paterson, Norman, and Mike Livesey
Evolving caching algorithms in C by genetic programming

Pelikan, Martin, Vladimir Kvasnicka, and Jiri Pospichal
Read's linear codes and genetic programming

Poli, Riccardo, and Stefano Cagnoni
Genetic Programming with User-Driven Selection: Experiments
on the Evolution of Algorithms for Image Enhancement

Poli, R., and W. B. Langdon
A New Schema Theory for Genetic Programming with One-
point Crossover and Point Mutation

Rosca, Justinian P.
Analysis of Complexity Drift in Genetic Programming

Ryan, Conor, and Paul Walsh
The Evolution of Provable Parallel Programs

Segovia, Javier, and Pedro Isasi
Genetic Programming For Designing Ad Hoc Neural Network
Learning Rules

Sherrah, Jamie R., Robert E. Bogner, and Abdesselam
The Evolutionary Pre-Processor: Automatic Feature Extraction
for Supervised Classification using Genetic Programming

Soule, Terence, and James A. Foster
Code Size and Depth Flows in Genetic Programming

Teller, Astro, and David Andre
Automatically Choosing the Number of Fitness Cases: The
Rational Allocation of Trials

Watson, Andrew H., and Ian C. Parmee
Steady State Genetic Programming With Constrained
Complexity Crossover

Winkeler, Jay F., and B. S. Manjunath
Genetic Programming for Object Detection

Zhang, Byoung-Tak, and Je-Gun Joung
Enhancing Robustness of Genetic Programming at the Species

Zhao, Kai and Jue Wang
"Chromosone-Protein'': A Representation Scheme


Bull, Larry, and Owen Holland
Evolutionary Computing in Multi-Agent Environments:

Cantu-Paz, Erick, an David E. Goldberg
Modeling Idealized Bounding Cases of Parallel Genetic

Dill, Karen M., and Marek A. Perkowski
Minimization of GRM Forms with a Genetic Algorithm

Gockel, Nicole, Martin Keim, Rolf Drechsler, and Bernd Becker
A Genetic Algorithm for Sequential Circuit Test Generation
based on Symbolic Fault Simulation

Kargupta, Hillol, David E. Goldberg, and Liwei Wang
Extending The Class of Order-k Delineable Problems For The
Gene Expression Messy Genetic Algorithm

Lathrop, James I.
Compression Depth and Genetic Programs

Mullen, David S., and Ralph M. Butler
Genetic Algorithms In Optimization of Adjacency Constrained
Timber Harvest Scheduling Problems

Yang, Jihoon, and Vasant Honavar
Feature Subset Selection Using A Genetic Algorithm


Balakrishnan, Karthik, and Vasant Honavar
Spatial Learning for Robot Localization

Floreano, Dario, and Stefano Nolfi
God Save the Red Queen! Competition in Co-Evolutionary

Hasegawa, Yasuhisa and Toshio Fukuda
Motion Generation of Two-link Brachiation Robot

Maeshiro, Tetsuya, and Masayuki Kimura
Genetic Code as an Evolving Organism

Ray, Thomas S.
Selecting Naturally for Differentiation


Angeline, Peter J.
An Alternative to Indexed Memory for Evolving Programs with
Explicit State Representations

Chellapilla, Kumar
Evolutionary Programming with Tree Mutations: Evolving
Computer Programs without Crossover

Greenwood, Garrison W.
Experimental Observation of Chaos in Evolution Strategies

Longshaw, Tom
Evolutionary learning of large Grammars


Arita, Masanori, Akira Suyama, and Masami Hagiya
A Heuristic Approach for Hamiltonian Path Problem with

Deaton, R, M. Garzon, R. C. Murphy, D. R. Francschetti,
J. A. Rose, and S. E. Stevens Jr.
Information Transfer through Hybridization Reactions in DNA
based Computing

Garzon, M., P. Neathery, R. Deaton, R. C. Murphy, D. R.
Franschetti, S. E. Stevens Jr.
A New Metric for DNA Computing

Rose, J. A., Y. Gao, M. Garzon, and R. C. Murphy
DNA Implementation of Finite-State Machines


Dreschler, Rolf, Nicole Gockel, Elke Mackensen, and
Bernd Becker
BEA: Specialized Hardware for Implementation of Evolutionary

Kazimierczak, Jan
An Approach to Evolvable Hardware representing the
Base in an Automatic Programming System

Michael Korkin, Hugo de Garis, Felix Gers, and Hitoshi Hemmi
``CBM (CAM-Brain Machine)'': A Hardware Tool which
Evolves a Neural Net Module in a Fraction of a Second and
Runs a Million Neuron Artificial Brain in Real Time

Liu, Weixin, Masahiro Murakawa, and Tetsuya Higuchi
Evolvable Hardware for On-line Adaptive Traffic Control in
ATM Networks

Sipper, Moshe, Eduardo Sanchez, Daniel Mange, Marco
Tomassini, Andres Perez-Uribe, and Andre Stauffer
The POE Model of Bio-Inspired Hardware Systems: A Short


Nagasaka, Ichiro, and Toshiharu Taura
Geometic Representation for Shape Generation using Classifier

Spohn, Bryan G., and Philip H. Crowley
Complexity of Strategies and the Evolution of Cooperation

Westerdale, T. H.
Classifier Systems--No Wonder They Don't Work



Koza, John R., Deb, Kalyanmoy, Dorigo, Marco, Fogel, David
B., Garzon, Max, Iba, Hitoshi, and Riolo, Rick L. (editors).
1997. Genetic Programming 1997: Proceedings of the
Second Annual Conference, July 13P16, 1997, Stanford
University. San Francisco, CA: Morgan Kaufmann.