Genetic and Evolutionary Computation COnference

GECCO-2005

Table of Contents

Author Index

Genetic Programming  

Exploiting Disruption Aversion to Control Bloat  (page 1605)
J. Stevens, R. B. Heckendorn, T. Soule (University of Idaho)

Finding Needles in Haystacks is Harder with Neutrality  (page 1613)
M. Collins (Edinburgh University)

Open-ended Robust Design of Analog Filters Using Genetic Programming  (page 1619)
J. Hu (Purdue University)
X. Zhong (Huzhang University of Sciences & Technology)
E. D. Goodman (Michigan State University)

Towards Identifying Populations that Increase the Likelihood 
of Success in Genetic Programming  (page 1627)
J. M. Daida (The University of Michigan)

Total Synthesis of Algorithmic Chemistries  (page 1635)
C. W. G. Lasarczyk (University of Dortmund)
W. Banzhaf (Memorial University of Newfoundland)

Multipopulation Cooperative Coevelutionary Programming (MCCP) 
to Enhance Design Innovation  (page 1641)
E. M. Zechman, S. R. Ranjithan (North Carolina State University)

Investigating the Performance of Module Acquisition in Cartesian Genetic Programming  (page 1649)
J. A. Walker, J. F. Miller (University of York)

Evolution of a Human-Competitive Quantum Fourier Transform 
Algorithm Using Genetic Programming  (page 1657)
P. Massey, J. A. Clark, S. Stepney (University of York)

meta-Grammar Constant Creation with Grammatical 
Evolution by Grammatical Evolution  (page 1665)                                            (Return to Top)
I. Dempsey, M. O'Neill (University of Limerick)
A. Brabazon (University College Dublin)

Resource-Limited Genetic Programming: The Dynamic Approach  (page 1673)
S. Silva, E. Costa (University of Coimbra)

Parsing and Translation of Expressions by Genetic Programming  (page 1681)
D. Jackson (University of Liverpool)

The Push3 Execution Stack and the Evolution of Control  (page 1689)
L. Spector, J. Klein (Hampshire College)
M. Keijzer (Chordiant Software Inc.)

CGP Visits the Santa Fe Trail — Effects of Heuristics on GP  (page 1697)
C. Z. Janikow, C. J. Mann (University of Missouri at St. Louis)

Genetic Network Programming with Automatically Defined Groups 
for Assigning Proper Roles to Multiple Agents  (page 1705)
T. Murata (Kansai University)
T. Nakamura (Kansai University Graduate School)

Probing for Limits to Building Block Mixing with a Tunably-Difficult 
Problem for Genetic Programming  (page 1713)
J. M. Daida, M. E. Samples, M. J. Byom (The University of Michigan)

Evolving Cooperative Strategies for UAV Teams  (page 1721)
M. D. Richards, D. Whitley, J. R. Beveridge (Colorado State University)
T. Mytkowicz (University of Colorado)
D. Nguyen, D. Rome (Raytheon/IIS/ Space Systems)

Measuring, Enabling and Comparing Modularity, Regularity 
and Hierarchy in Evolutionary Design  (page 1729)
G. S. Hornby (NASA Ames Research Center)

Evolving Fuzzy Decision Tree Structure that Adapts in Real-Time  (page 1737)
J. F. Smith III (Naval Research Laboratory)

Dormant Program Nodes and the Efficiency of Genetic Programming  (page 1745)
D. Jackson (University of Liverpool)

Multi-Chromosomal Genetic Programming  (page 1753)
R. Cavill, S. Smith, A. Tyrrell (University of York)

Molecular Programming: Evolving Genetic Programs in a Test Tube  (page 1761)
B.-T. Zhang, H.-Y. Jang (Seoul National University)

Genetic Programming: Posters                                                               (Return to Top)

Function Choice, Resiliency and Growth in Genetic Programming  (page 1771)
S. Besetti, T. Soule (University of Idaho)

Evaluating GP Schema in Context  (page 1773)
H. Majeed, C. Ryan, R. M. A. Azad (University of Limerick)

Probabilistic Distribution Models for EDA-based GP  (page 1775)
K. Yanai, H. Iba (The University of Tokyo)

Backward-chaining Genetic Programming  (page 1777)
R. Poli, W. B. Langdon (University of Essex)

Preventing Overfitting in GP with Canary Functions  (page 1779)
N. Foreman (Altarum Institute)
M. Evett (Eastern Michigan University)

An Investigation into Using Genetic Programming as a Means of Inducing Solutions to Novice Procedural Programming Problems  (page 1781)
N. Pillay (University of KwaZulu-Natal)

A Statistical Learning Theory Approach of Bloat  (page 1783)
S. Gelly, O. Teytaud, N. Bredeche, M. Schoenauer (University Paris-Sud)

Scalability of Genetic Programming and Probabilistic Incremental 
Program Evolution  (page 1785)
R. Ondas, M. Pelikan (University of Missouri at St. Louis)
K. Sastry (University of Illinois at Urbana-Champaign)

Evolving Recurrent Models Using Linear GP  (page 1787)
X. Luo, M. I. Heywood, A. N. Zincir-Heywood (Dalhousie University)

Evolutionary Tree Genetic Programming  (page 1789)
J. Antolík (Charles University)
W. H. Hsu (Kansas State University)

Parameter Sweeps for Exploring GP Parameters  (page 1791)
M. E. Samples, J. M. Daida, M. Byom, M. Pizzimenti (University of Michigan)