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GP-97 Call for Participation / List of 84 Papers

John Koza koza at CS.Stanford.EDU
Sat May 10 16:21:31 EST 1997


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)
WWW FOR GP-97: http://www-cs-faculty.stanford.edu/~koza/gp97.html
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 
(http://www.sciam.com/WEB/1096issue/1096techbus3.html).  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: http://www-cs-faculty.stanford.edu/~koza/gp97.html  E-
 MAIL:  gp at aaai.org.  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 scltravel at cgl.com.If 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 http://www.stanford.edu/, the Hyperion Guide at 
 http://www.hyperion.com/ba/sfbay.html; the Palo Alto weekly at 
 http://www.service.com/PAW/home.html; the California Virtual Tourist at 
 http://www.research.digital.com/SRC/virtual-tourist/California.html; 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 
 (http://www.siam.org).  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  
 http://www.cs.cmu.edu/afs/cs/project/space/www/cira97/conference.html.   Other 
 non-California conferences of interest include AAAI-97 on July 27-31, 1997 in 
 Providence, Rhode Island (http://www.aaai.org/); ICGA-97 on July 20-23, 1997 
 in East Lansing, Michigan (http://isl.cps.msu.edu/GA/icga97); European 
 Artificial Life Conference on July 28-31, 1997 in Brighton, England 
 (http://www.cogs.susx.ac.uk/ecal97/); and IJCAI-97 on August 26-29, 1997 in 
 Nagoya, Japan (http://www.aaai.org/). 
 MEMBERSHIP IN THE ACM, AAAI, or SIAM:  For information about ACM membership, 
 go to http://www.acm.org/; for SIGART, http://sigart.acm.org/; for AAAI 
 http://www.aaai.org/; and for SIAM, http://www.siam.org.  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:   gp at aaai.org.  WWW FOR AAAI: 
 http://www.aaai.org/.  WWW FOR GP-97: http://www-cs-

 REGISTRATION FORM FOR genetic programming 1997 CONFERENCE

 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: gp at aaai.org.  WWW FOR AAAI: http://www.aaai.org/.   
 WWW FOR GP-97: http://www-cs-faculty.stanford.edu/~koza/gp97.html 


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. 

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