The GP-96 Late-Breaking Papers Book is available directly from
the Stanford Bookstore
In order to provide conference attendees at the Genetic
Programming 1996 Conference (GP-96) held at Stanford
University on July 28 ­p; 31, 1996 (Sunday ­p; Wednesday) with
information about research that was initiated, enhanced,
improved, or completed after the original paper submission
deadline of January 10, 1996, this rapidly-printed book of 27
late-breaking papers is being distributed to all attendees (in
addition to the peer-reviewed conference proceedings book published by the
MIT Press). Late-breaking papers were briefly examined for minimum
standards of acceptability and relevance, but were not peer
reviewed or evaluated by the conference organizers.
This 210-page volume (ISBN 0-18-201-031-7) may be purchased directly from
the Custom Publishing Department of the Stanford
University Bookstore
by calling 415-329-1217 or 800-533-2670 or by
writing Custom Publishing Department, Stanford Bookstore,
Stanford University, Stanford, California 94305-3079 USA.
The E-Mail address of the bookstore for mail orders is
mailorder@bookstore.stanford.edu. The WWW URL for the Stanford Bookstore
is http://bookstore.stanford.edu
/. The price is
$9.54 plus $6.00 shipping and handling (in the USA).
California residents must add appropriate sales tax.
27 GP-96 Late-Breaking Papers...
A Platform-Independent Collaborative Interface for
Genetic Programming Applications: Image Analysis for
Scientific Inquiry
Tommaso F. Bersano-Begey, Jason M. Daida, John F.
Vesecky and Frank L. Ludwig
Genetic Search of Reliable Encodings for DNA-Based
Computation
R. Deaton, M. Garzon, R. C. Murphy, J. A. Rose, D. R.
Franceschetti, and S. E. Stevens, Jr.
Evolutionary Algorithms for Natural Language Processing
Ted E. Dunning and Mark W. Davis
Some Applications of Genetic Programming in Digital
Signal Processing
Anna I. Esparcia Alcazar and Ken C. Sharman
Nonlinear Model Structure Identification Using Genetic
Programming
Gary J. Gray, David J. Murray-Smith, Yun Li, and Ken. C.
Sharman
Collective Memory Search
Thomas Haynes
Cooperation of the Fittest
Thomas Haynes and Sandip Sen
Modelling Chemical Process Systems Using a Multi-Gene
Genetic Programming Algorithm
Mark Hinchliffe, Hugo Hiden, Ben McKay, Mark Willis,
Ming Tham, and Geoffery Barton
Emergent Cooperation for Multiple Agents using Genetic
Programming
Hitoshi Iba
Random Tree Generation for Genetic Programming
Hitoshi Iba
An Adaptive Genetic Algorithm for Image Data
Compression
J. Jiang and D. Butler
Contest Length, Noise, and Reciprocal Altruism in the
Population of a Genetic Algorithm for the Iterated
Prisoner's Dilemma
Bryant A. Julstrom
Evolution of a Low-Distortion, Low-Bias 60 Decibel Op
Amp with Good Frequency Generalization using Genetic
Programming
John R. Koza, David Andre, Forrest H Bennett III, and
Martin A. Keane
Evolutionary and Incremental Methods to Solve Hard
Learning Problems
Ibrahim Kuscu
Scheduling Maintenance of Electric Power Transmission
Networks Using Genetic Programming
W. B. Langdon
Evolving Graphs and Networks with Edge Encoding:
Preliminary Report
Sean Luke and Lee Spector
Why Might Some Problems Be Difficult for Genetic
Programming to Find Solutions?
S. R. Maxwell
Capturing Preference into a Function using Interactions
with a Manual Evolutionary Design Aid System
Yasuto Nakanishi
Distinguishing Genotype and Phenotype in Genetic
Programming
Norman R. Paterson and Mike Livesey
Implicit versus Explicit: A Comparison of State in Genetic
Programming
Simon E.Raik and David G. Browne
A New Uniform Order-Based Crossover Operator for
Multi-Component Combinatorial Optimization Problems
Funda Sivrikaya-Serifoglu and Gunduz Ulusoy
Conjugation _ A Bacterially Inspired Form of Genetic
Recombination
Peter Smith
An Individually Variable Mutation-Rate Strategy for
Genetic Algorithms
Stephen A. Stanhope and Jason M. Daida
Neural Programming and an Internal Reinforcement
Policy
Astro Teller and Manuela Veloso
Genetic Programming without Fitness
Andrea G. B.Tettamanzi
Building Software Agents for Information Filtering on the
Internet: A Genetic Programming Approach
Byoung-Tak Zhang, Ju-Hyun Kwak, and Chang-Hoon Lee
Emotional Expression Classification by Genetic
Programming
Jun Zhao, Garrett Kearney, and Alan Soper
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