VOLUME 2 CONTENTS GENETIC PROGRAMMING AND EVOLVABLE HARDWARE Coevolving Functions in Genetic Programming: Classification using K­nearest­neighbour Manu Ahluwalia and Larry Bull . . . . . . . . . . . . . . . 947 Discovering comprehensible classification rules by using Genetic Programming: a case study in a medical domain Celia C. Bojarczuk, Heitor S. Lopes, and Alex A. Freitas . . . . . . . . . . . . . . . . . . . . . . . . . . 953 Evolutionary Modeling of Ordinary Differential Equations for Dynamic Systems Hongqing Cao, Lishan Kang, and Yuping Chen . . . . . 959 Towards an Agent­Based Foundation of Financial Econometrics: An Approach Based on Genetic­Programming Artificial Markets Shu­Heng Chen and Tzu­Wen Kuo . . . . . . . . . . . . . . 966 Individual GP: an Alternative Viewpoint for the Resolution of Complex Problems Pierre Collet, Evelyne Lutton, Frédéric Raynal, and Marc Schoenauer . . . . . . . . . . . . . . . . . . . . . . . . 974 What Makes a Problem GP­Hard? Analysis of a Tunably Difficult Problem in Genetic Programming Jason M. Daida, John A. Polito, Steven A. Stanhope, Robert R. Bertram, Jonathan C. Khoo, and Shahbaz A. Chaudhary . . . . . . . . . . . . . . . . . . . 982 Rule Induction Using a Reverse Polish Representation G. F. Davenport, M. D. Ryan, and V. J. Rayward­Smith . . . . . . . . . . . . . . . . . . . . . 990 An Analysis of Automatic Subroutine Discovery in Genetic Programming Antonello Dessì, Antonella Giani, and Antonia Starita . . . . . . . . . . . . . . . . . . . . . . . . . 996 Dynamical Properties of the Fitness Landscape of a GP Controlled Random Morphology Robot Peter Dittrich, Andre Skusa, Wolfgang Kantschik, and Wolfgang Banzhaf . . . . . . . . . . . . . . . . . . . . . . 1002 Evolving a behavior­based control architecture--- From simulations to the real world Marc Ebner and Andreas Zell . . . . . . . . . . . . . . . . . 1009 A Cellular Genetic Programming Approach to Classification Gianluigi Folino, Clara Pizzuti, and Giandomenico Spezzano . . . . . . . . . . . . . . . . . 1015 Homologous Crossover in Genetic Programming Frank D. Francone, Markus Conrads, Wolfgang Banzhaf, and Peter Nordin . . . . . . . . . . . . 1021 Generating Lemmas for Tableau­based Proof Search Using Genetic Programming Marc Fuchs, Dirk Fuchs, and Matthias Fuchs . . . . . 1027 Large Populations Are Not Always The Best Choice In Genetic Programming Matthias Fuchs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1033 Emergence of the cooperative behavior using ADG; Automatically Defined Groups Akira Hara and Tomoharu Nagao . . . . . . . . . . . . . . 1039 A Staged Genetic Programming Strategy for Image Analysis Daniel Howard and Simon C. Roberts . . . . . . . . . . . 1047 Bagging, Boosting, and Bloating in Genetic Programming Hitoshi Iba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1053 Investigating the Influence of Depth and Degree of Genotypic Change on Fitness in Genetic Programming Christian Igel and Kumar Chellapilla . . . . . . . . . . . 1061 Dimensionally Aware Genetic Programming Maarten Keijzer and Vladan Babovic . . . . . . . . . . . 1069 The Evolution of Genetic Code in Genetic Programming Robert E. Keller and Wolfgang Banzhaf . . . . . . . . . . 1077 Searching for the Impossible using Genetic Programming John R. Koza, Martin A. Keane, Forrest H Bennett III, Jessen Yu, William Mydlowec, and Oscar Stiffelman . . . . . . . . . . . . . . . . . . . . . . . . 1083 Size Fair and Homologous Tree Genetic Programming Crossovers W. B. Langdon . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1092 ``Genetic'' Programming Sean Luke, Shugo Hamahashi, and Hiroaki Kitano . . . . . . . . . . . . . . . . . . . . . . . . . 1098 Non­Linear Continuum Regression Using Genetic Programming Ben McKay, Mark Willis, Dominic Searson, and Gary Montague . . . . . . . . . . . . . . . . . . . . . . . . 1106 Analysis of genetic diversity through population history Nicholas Freitag McPhee and Nicholas J. Hopper . . . . . . . . . . . . . . . . . . . . . . 1112 Random Generator Quality and GP Performance Mark M. Meysenburg and James A. Foster . . . . . . . 1121 Digital Filter Design at Gate­level using Evolutionary Algorithms Julian F. Miller . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1127 An empirical study of the efficiency of learning boolean functions using a Cartesian Genetic Programming approach Julian F. Miller . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1135 Under the Hood of Grammatical Evolution Michael O'Neill and Conor Ryan . . . . . . . . . . . . . . 1143 Graph Based Crossover---A Case Study with the Busy Beaver Problem Francisco B. Pereira, Penousal Machado, Ernesto Costa, and Amílcar Cardoso . . . . . . . . . . . . 1149 Evolving Effective Visual Tracking through Shaping Simon Perkins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1156 Smooth Uniform Crossover, Sub­Machine Code GP and Demes: A Recipe For Solving High­Order Boolean Parity Problems Riccardo Poli, Jonathan Page, and W. B. Langdon . . . . . . . . . . . . . . . . . . . . . . . . . 1162 Evolution of Neural Networks Using Weight Mapping João Carlos Figueira Pujol and Riccardo Poli . . . . . . 1170 Evolutionary Discovery of Learning Rules for Feedforward Neural Networks with Step Activation Function Amr Radi and Riccardo Poli . . . . . . . . . . . . . . . . . . 1178 Sequence Learning Through PIPE and Automatic Ta s k D e c o m p o s t i o n Rafal P. Salustowicz and Jürgen Schmidhuber . . . . . 1184 Optical Mesh Network Topology Design using Node­Pair Encoding Genetic Programming Mark C. Sinclair . . . . . . . . . . . . . . . . . . . . . . . . . . 1192 Evolution of CMOS Circuits in Simulations and Directly in Hardware on a Programmable Chip Adrian Stoica, Carlos­Salazar Lazaro, Didier Keymeulen, and Ken Hayworth . . . . . . . . . . 1198 An Evolvable­hardware­based Clock Timing Architecture towards GigaHz Digital Systems Eiichi Takahashi, Masahiro Murakawa, Kenji Toda, and Tetsuya Higuchi . . . . . . . . . . . . . . . . . . . . . . . . 1204 A Functional Style and Fitness Evaluation Scheme for Inducting High Level Programs Paul Walsh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1211 Genetic Programming with Incremental Data Inheritance Byoung­Tak Zhang and Je­Gun Joung . . . . . . . . . . . 1217 GENETIC PROGRAMMING AND EVOLVABLE HARDWARE, POSTER PAPERS Evolutionary Multimodel Partitioning Filters for Nonlinear Systems G. N. Beligiannis, E. N. Demiris, and S. D. Likothanassis . . . . . . . . . . . . . . . . . . . . . . 1227 Parallel Machine Code Genetic Programming Markus Brameier, Frank Hoffmann, Peter Nordin, Wolfgang Banzhaf, and Frank Francone . . . . . . . . . . 1228 Java based Distributed Genetic Programming on the Internet Fuey Sian Chong and W. B. Langdon . . . . . . . . . . . . 1229 N­Dimensional Surface Mapping Using Genetic Programming David Corney and Ian Parmee . . . . . . . . . . . . . . . . 1230 Evolving Scheduling Policies through a Genetic Programming Framework Christos Dimopoulos and Ali MS Zalzala . . . . . . . . 1231 Modelling software quality with GP Matthew Evett, Taghi Khoshgoftaar, Pei­der Chien, and Edward Allen . . . . . . . . . . . . . . . . . . . . . . . . . . 1232 ATR's Artificial Brain (``CAM­Brain'') Project: A Sample of What Individual ``CoDi­1Bit'' Model Evolved Neural Net Modules Can Do with Digital and Analog I/O H. de Garis, A. Buller, M. Korkin, F. Gers, N. E. Nawa, and M. Hough . . . . . . . . . . . . . . . . . . 1233 Towards Byte Code Genetic Programming Brad Harvey, James Foster, and Deborah Frincke . . . 1234 Evolution of the Digital Circuits with Variable Layouts Tatiana Kalganova, Julian F. Miller, and Terence C. Fogarty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1235 Logic­based Genetic Programming with Definite Clause Translation Grammars Brian J. Ross . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1236 Constructive Induction of Fuzzy Cartesian Granule Feature Models using Genetic Programming James G. Shanahan, James F. Baldwin, and Trevor P. Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1237 Result­Sharing: A Framework for Cooperation in Genetic Programming Edgar E. Vallejo and Fernando Ramos . . . . . . . . . . . 1238 ARTIFICIAL LIFE, ADAPTIVE BEHAVIOR AND AGENTS Heterochrony and Adaptation in Developing Neural Networks Angelo Cangelosi . . . . . . . . . . . . . . . . . . . . . . . . . . . 1241 Aircraft Maneuvering via Genetics­Based Adaptive Agent H. Brown Cribbs, III . . . . . . . . . . . . . . . . . . . . . . . . 1249 Population dynamics and emerging mental features in AEGIS A. E. Eiben, D. Elia, and J. I. van Hemert . . . . . . . 1257 Modeling of Complex Economic Systems with Agent Nets Alexei A. Gaivoronski . . . . . . . . . . . . . . . . . . . . . . . 1265 Evolution and Analysis of Dynamical Neural Networks for Agents Integrating Vision, Locomotion, and Short­Term Memory John C. Gallagher and Randall D. Beer . . . . . . . . . 1273 Evolution of Goal­Directed Behavior from Limited Information in a Complex Environment Matthew R. Glickman and Katia Sycara . . . . . . . . . 1281 Immunity by Design: An Artificial Immune System Steven A. Hofmeyr and Stephanie Forrest . . . . . . . . 1289 Autonomous Evolution of Gaits with the Sony Quadruped Robot G. S. Hornby, M. Fujita, S. Takamura, T. Yamamoto, and O. Hanagata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1297 Diffuse versus True Coevolution in a Physics­based Wor l d Gregory S. Hornby and Brian Mirtich . . . . . . . . . . . 1305 (formerly ES­212) Non­reciprocal Altruism and the Evolution of Paternal Care Cathy Key . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1313 A PATCHWORK Model for Evolutionary Algorithms with Structured and Variable Size Populations Thiemo Krink, Brian H. Mayoh, and Zbigniew Michalewicz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1321 How Not to Be a Black­Box: Evolution and Genetic­Engineering of High­Level Behaviours Ik Soo Lim and Daniel Thalmann . . . . . . . . . . . . . 1329 Four Steps Toward Open­Ended Evolution C. C. Maley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1336 Evolutionary Optimization Through Extinction Dynamics Jesús Marín and Ricard V. Solé . . . . . . . . . . . . . . . . 1344 Coupling Morphology and Control in a Simulated Robot Craig Mautner and Richard K. Belew . . . . . . . . . . . 1350 An Approach to Solving Combinatorial Optimization Problems Using a Population of Reinforcement Learning Agents Victor V. Miagkikh and William F. Punch III . . . . . 1358 A Generic Neutral Model for Measuring Excess Evolutionary Activity of Genotypes Andreas Rechsteiner and Mark A. Bedau . . . . . . . . . 1366 Persistence, Search and Autopoiesis Oliver Sharpe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1374 Effect of Mutation and Recombination on the Genotype­Phenotype Map C. R. Stephens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1382 Evaluation Criteria for Genetically­Tuned Problem­Solving Experts David Sturgill and Gautam Pant . . . . . . . . . . . . . . . 1390 How to Design Good Learning Agents in Organization Keiki Takadama, Takao Terano, and Katsunori Shimohara . . .1398 Cooperative and Competitive Behavior Acquisition for Mobile Robots through Co­evolution Eiji Uchibe, Masateru Nakamura, and Minoru Asada . . . . .. . . .1406 Evolutionary Behaviors Emerged through Strategic Interactions in the Large Kimitaka Uno and Akira Namatame . . . . . . . . . . . . 1414 Simulating exploratory behavior in evolving Neural Networks Richard Walker and Orazio Miglino . . . . . . . . . . . . . 1422 Two Evolutionary Representations for Automatic Parallelization Kenneth P. Williams and Shirley A. Williams . . . . . . 1429 ARTIFICIAL LIFE, ADAPTIVE BEHAVIOR AND AGENTS, POSTER PAPERS Behavior­Based Control System in MultiAgent Domain Stéphane Calderoni . . . . . . . . . . . . . . . . . . . . . . . . . 1439 Evolutionary Algorithm Analysis of the Biological Genetic Codes David Digby and William Seffens . . . . . . . . . . . . . . . 1440 Distributed Genetic Programming with Mobile Agents Robert Ghanea­Hercock, Divine T. Ndumu, and Jaron Collis . . . . . . . . . . . . . . . . . . . . . . . . . . . 1441 A Comparison of Some Methods for Evolving Neural Networks Marko Grönroos . . . . . . . . . . . . . . . . . . . . . . . . . . . 1442 Evolutionary Cellular Automata for Optimal Path Planning of Mobile Robots Yong­Gun Jo and Hoon Kang . . . . . . . . . . . . . . . . . 1443 In real or artificial life, Is Evolutionary Progress in a Closed System Possible? Brig Klyce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1444 Sequential Dynamical Systems and Simulation Stephan Kopp, Henning S. Mortveit, and Christian M. Reidys . . . . . . . . . . . . . . . . . . . . . . 1445 Complexity in Mate Choice Patricio Lerena and Michèle Courant . . . . . . . . . . . . 1446 Effects of ``Physical Body'' on Biased Opponent Selection in the Iterated Prisoner's Dilemma Game Jae C. Oh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1447 Genetically Programming Networks to Evolve Memory Mechanisms Arlindo Silva, Ana Neves, and Ernesto Costa . . . . . . 1448 Adaptive Behavior of Incrementally Evolved Neural Networks based on Cellular Automata Geum­Beom Song and Sung­Bae Cho . . . . . . . . . . . 1449 Practical and Theoretical Investigation of a Collective work Yasuhiro Suzuki and Hiroshi Tanaka . . . . . . . . . . . 1450 A Simulation Study on Adaptive Behavior of Fish Schools under Environmental Variation Yajie Tian, Nobuo Sannomiya, and Toru Yokokura . . . . . . . . . . . . . . . . . . . . . . . . . 1451 Further Investigations into the Evolution of Agents with Concurrent Genetic Programming Adrian Trenaman . . . . . . . . . . . . . . . . . . . . . . . . . . 1452 Application Oriented Routing with Biologically­inspired Agents Tony White and Bernard Pagurek . . . . . . . . . . . . . . 1453 REAL WORLD APPLICATIONS Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks Adam V. Adamopoulos, Efstratios F. Georgopoulos, Spiridon D. Likothanassis, and Photios A. Anninos . . . . . . . . . . . . . . . . . . . . . 1457 Genetic Programming of Full Knowledge Bases for Fuzzy Logic Controllers Daryl Battle, Abdollah Homaifar, Edward Tunstel, and Gerry Dozier . . . . . . . . . . . . . . . . . . . . . . . . . . 1463 Extending the bounds of the search space: A Multi­Population approach M. A. Beck and I. C. Parmee . . . . . . . . . . . . . . . . . 1469 Evolution by Means of Genetic Programming of Analog Circuits that Perform Digital Functions Forrest H Bennett III, John R. Koza, Martin A. Keane, Jessen Yu, William Mydlowec, and Oscar Stiffelman . . . . . . . . . . . . . . . . . . . . . . . 1477 Building a Parallel Computer System for $18,000 that Performs a Ha l f Peta­Flop per Day Forrest H Bennett III, John R. Koza, James Shipman, and Oscar Stiffelman . . . . . . . . . . . . . . . . . . . . . . . 1484 An Investigation of Exploration and Exploitation Within Cluster Oriented Genetic Algorithms (COGAs) Christopher R. Bonham and Ian C. Parmee . . . . . . 1491 Modified Gradient Techniques for Normalized Solution Vectors Kelly D. Crawford, Michael D. McCormack, and Donald J. MacAllister . . . . . . . . . . . . . . . . . . . 1498 Use of Preferences for GA­based Multi­objective Optimisation Dragan Cvetkovic and Ian C. Parmee . . . . . . . . . . . 1504 Infrastructure Work Order Planning Using Genetic Algorithms E. William East . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1510 A Biologically Inspired Fitness Function for Robotic Grasping J. Jaime Fernandez Jr. and Ian D. Walker . . . . . . . . 1517 A Particle Swarm Optimization for Reactive Power and Voltage Control in Electric Power Systems Yoshikazu Fukuyama, Shinichi Takayama, Yosuke Nakanishi, and Hirotaka Yoshida . . . . . . . . . 1523 Plasma X­ray Spectra Analysis Using Genetic Algorithms Igor E. Golovkin, Roberto C. Mancini, and Sushil J. Louis . . . . . . . . . . . . . . . . . . . . . . . . . 1529 A Tool for Solving Differential Games with Co­evolutionary Algorithms Francisco Gordillo, Ismael Alcalá, and Javier Aracil . . . . . . . . . . . . . . . . . . . . . . . . . . . 1535 India and Pakistan, a classic ``Richardson'' Arms Race: A Genetic Algorithmic approach Tim Hackworth . . . . . . . . . . . . . . . . . . . . . . . . . . . 1543 Evaluation of Alternative Penalty Function Implementations in a Watershed Management Design Problem Laura J. Harrell and S. Ranji Ranjithan . . . . . . . . . 1551 An Immune System Approach to Scheduling in Changing Environments Emma Hart and Peter Ross . . . . . . . . . . . . . . . . . . . 1559 Solving Large Knowledge Base Partitioning Problems Using an Intelligent Genetic Algorithm Shinn­Ying Ho, Hung­Ming Chen, and Li­Sun Shu . . . . . . . . . . . . . . . . . . . . . . . . . . . 1567 Genetic Algorithm for Regional Surveillance Maria John, David Panton, and Kevin White . . . . . 1573 Magnetotelluric Inversion Using Problem­Specific Genetic Operators Pedro Luis Kantek Garcia Navarro, Pedro P. B. de Oliveira, Fernando M. Ramos, and Haroldo F. Campos­Velho . . . . . . . . . . . . . . . . . 1580 Parametric L­System Description of the Retina with Combined Evolutionary Operators Gabriella Kókai, Róbert Ványi, and Zoltán Tóth . . . 1588 Protein Structure Prediction With Evolutionary Algorithms Natalio Krasnogor, William E. Hart, Jim Smith, and David A. Pelta . . . . . . . . . . . . . . . . . . . . . . . . . 1596 A Multilevel k­way Partitioning Algorithm for Finite Element Meshes using Competing Ant Colonies A. E. Langham and P. W. Grant . . . . . . . . . . . . . . . 1602 Coevolution with the Genetic Algorithm: Repeated Differentiated Oligopolies Robert E. Marks, David F. Midgley, Lee G. Cooper, and G. M. Shiraz . . . . . . . . . . . . . . . . . . . . . . . . . . 1609 Scalable Search Spaces for Scheduling Problems Dirk C. Mattfeld . . . . . . . . . . . . . . . . . . . . . . . . . . 1616 Independent and Simultaneous Evolution of Fuzzy Sleep Classifiers by Genetic Algorithms Cristina Mota, Heitor Ferreira, and Agostinho Rosa . . . . . . . . . . . . . . . . . . . . . . . . . 1622 PROGEN: a Genetic­Based Semi­automatic Hypertext Construction Tool---first steps and experiment Georges Nault, Vincent Rialle, and Jean­Guy Meunier . . . . . . . . . . . . . . . . . . . . . . 1630 Using Evolutionary Algorithms in the Design of Protein Fingerprints Björn Olsson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1636 Hazard Assessment Modeling: An Evolutionary Ensemble Approach David W. Opitz, Subhash C. Basak, and Brian D. Gute . . . . . . . . . . . . . . . . . . . . . . . . . 1643 How the immune system generates diversity: Pathogen space coverage with random and evolved antibody libraries Mihaela Oprea and Stephanie Forrest . . . . . . . . . . . 1651 Preliminary Airframe Design Using Co­Evolutionary Multiobjective Genetic Algorithms Ian C. Parmee and Andrew H. Watson . . . . . . . . . . 1657 Using Genetic Algorithm to manipulate polynomial expressions Andrzej J. Pindor . . . . . . . . . . . . . . . . . . . . . . . . . . 1666 Optimal Control of Greenhouse Climate using Real­World Weather Data and Evolutionary Algorithms Hartmut Pohlheim and Adolf Heiner . . . . . . . . . . 1672 Design of a Genetic­Fuzzy System for Planning Optimal Path and Gait Simultaneously of a Six­legged Robot Dilip Kumar Pratihar, Kalyanmoy Deb, and Amitabha Ghosh . . . . . . . . . . . . . . . . . . . . . . . . 1678 Prediction of Silicon Content of Hot Metal Using Fuzzy­GA Regression Sheel Punya and Brahma Deo . . . . . . . . . . . . . . . . . 1685 Frame Design Synthesis Using Implicit Redundant Genetic Algorithm Anne M. Raich and Jamshid Ghaboussi . . . . . . . . . . 1691 Automatic Graph Drawing and Stochastic Hill Climbing Alejandro Rosete­Suárez, Alberto Ochoa­Rodríguez, and Michele Sebag . . . . . . . . . . . . . . . . . . . . . . . . . 1699 A Hybrid Genetic Algorithm for the Fixed Channel Assignment Problem Mark Ryan, Justin Debuse, George Smith, and Ian Whittley . . . . . . . . . . . . . . . . . . . . . . . . . . . 1707 Object­based Design Modeling and Optimization with Genetic Algorithms Nicola Senin, David R. Wallace, and Nick Borland . . . . . . . . . . . . . . . . . . . . . . . . . . 1715 Optimization by Searching a Tree of Populations Louis Steinberg and Khaled Rasheed . . . . . . . . . . . . 1723 Modelling and Forecasting of Glaucomatous Visual Fields Using Genetic Algorithms Stephen Swift and Xiaohui Liu . . . . . . . . . . . . . . . . 1731 Directed Multiple Objective Search of Design Spaces Using Genetic Algorithms and Neural Networks David S. Todd and Pratyush Sen . . . . . . . . . . . . . . . 1738 Evolutionary Divide and Conquer (II) for the TSP Christine L. Valenzuela . . . . . . . . . . . . . . . . . . . . . . 1744 Assessment of the Web using Genetic Programming Reginald L. Walker . . . . . . . . . . . . . . . . . . . . . . . . . 1750 Evolutionary Programming Based Method for Evaluation of Power Flow Kit Po Wong, Jason Yuryevich, and An Li . . . . . . . . . 1756 Evolutionary Algorithm Based Exploration of Software Schedules for Digital Signal Processors Eckart Zitzler, Jürgen Teich, and Shuvra S. Bhattacharyya . . . . . . . . . . . . . . . . . . 1762 REAL WORLD APPLICATIONS, POSTER PAPERS GAs in Global Optimization of Mixed Integer Non­Linear Problems Lino Costa and Pedro Oliveira . . . . . . . . . . . . . . . . 1773 Control System Optimization Using Genetic Algorithms within the SoftLab Toolkit Lisa M. Desjarlais, Mohammad­R. Akbarzadeh­T., and Craig W. Wright. . . . . . . . . . . . . . . . . . . . . . . . . 1774 Real­World Applications. Optimising the throughput of a manufacturing production line using a genetic algortihm R. Dupas, G. Cavory, and G. Goncalves . . . . . . . . . 1775 Real­world applications: Motion planning using GAs Craig Eldershaw and Stephen Cameron . . . . . . . . . . 1776 Evolutionary Algorithm for School Timetabling Carlos Fernandes, João Paulo Caldeira, Fernando Melicio, and Agostinho Rosa . . . . . . . . . . . 1777 Road Design by Evolutionary Modelling of Routes Ângela Guimarães Pereira . . . . . . . . . . . . . . . . . . . . . 1778 Parameter Identification Within Rocks Using Genetic Algorithms S. D. Harris, R. Mustata, L. Elliott, D. B. Ingham, and D. Lesnic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1779 The Retrieval of Chemical Reaction Rates Using Genetic Algorithms S. D. Harris, L. Elliott, D. B. Ingham, M. Pourkashanian, and C. W. Wilson . . . . . . . . . . . . . . 1780 Feature Selection Using a Genetic Algorithm for Intrusion Detection Guy Helmer, Johnny Wong, Vasant Honavar, and Les Miller . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1781 Dynamic Chemical Process Modelling Using a Multiple Basis Function Genetic Programming Algorithm Mark Hinchliffe, Mark Willis, and Ming Tham . . . 1782 Genetic Algorithms for Attribute Synthesis in Large­Scale Data Mining William H. Hsu, William M. Pottenger, Michael Welge, Jie Wu, and Ting­Hao Yang . . . . . . . 1783 Genetic Algorithm for a Large­Scale Scheduling Problem in an Electric Wire Production Process Hitoshi Iima and Nobuo Sannomiya . . . . . . . . . . . . 1784 Modeling A Grinding Circuit Using Genetic Programming Charles L. Karr and Ken Borgelt . . . . . . . . . . . . . . . 1785 Solutions to Systems of Nonlinear Equations Via Genetic Algorithm Charles L. Karr and Barry Weck . . . . . . . . . . . . . . . 1786 Solving Wood Collection Problem using Genetic Algorithms Ilkka Karanta, Topi Mikkola, Catherine Bounsaythip, Olli Jokinen, and Juha Savola . . . . . . . . . . . . . . . . . 1787 Incorporating Human Preference into Content­based Image Retrieval Using Interactive Genetic Algorithm Joo­Young Lee and Sung­Bae Cho . . . . . . . . . . . . . . 1788 Multiobjective Genetic Algorithm for Rolling­Horizon Production Planning Y. Li, K. F. Man, and K. S. Tang . . . . . . . . . . . . . . 1789 Improving Parallel Ordering of Sparse Matrices using Genetic Algorithms Wen­Yang Lin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1790 Evolutionary Computation of Supersonic Wing Shape Optimization Shigeru Obayashi, Daisuke Sasaki, and Yukihiro Takeguchi . . . . . . . . . . . . . . . . . . . . . . 1791 Analysis of Genetic Algorithms Convergence Applied to Mensuration Problems in Computer Vision Gustavo Olague . . . . . . . . . . . . . . . . . . . . . . . . . . . 1792 Optimization of GA Parameters to Train Recurrent ANN through Weight Adjustment and Selection of Activation Functions Alejandro Pazos, Julián Dorado, Antonino Santos, and Juan Ramón Rabuñal . . . . . . . . . . . . . . . . . . . 1793 Adaptive Aspects of Rhythmic Composition: Genetic Music Alejandro Pazos, A. Santos del Riego, Julián Dorado, and J. J. Romero Cardalda . . . . . . . . . . . . . . . . . . . 1794 Testing the Temporal Behavior of Real­Time Software Modules using Extended Evolutionary Algorithms Hartmut Pohlheim and Joachim Wegener . . . . . . . . . 1795 Modelling Antibiotic Production using Standard and Sequential Hybridised Symbolic Annealing Mark A. Porter, Mark J. Willis, and Gary A. Montague . . . . . . . . . . . . . . . . . . . . . . 1796 A Fuzzy Neighborhood Based GA in Fuzzy Engineering Design Ralf Schleiffer and Hans­Jürgen Sebastian . . . . . . . . 1797 An Application of Genetic Programming To Investment System Optimization Charles E. Smith . . . . . . . . . . . . . . . . . . . . . . . . . . . 1798 Evolutionary Algorithms for Optimizing Speech Data Projection A. Spalanzani, S. A. Selouani, and H. Kabré . . . . . 1799 Feature Subset Selection for Rule Induction Using RIPPER Jihoon Yang, Asok Tiyyagura, Fajun Chen, and Vasant Honavar . . . . . . . . . . . . . . . . . . . . . . . . 1800 DNA AND MOLECULAR COMPUTING Reaction Temperature Constraints in DNA Computing Russell Deaton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1803 On Self­Assembling Graphs in vitro Max H. Garzon, Russell J. Deaton, and Ken Barnes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1805 Virtual DNA Simulator and Protocol Design by GA Akio Nishikawa, Masami Hagiya, and Masayuki Yamamura . . . . . . . . . . . . . . . . . . . . 1810 Relating the Minimum Model for DNA Computation and Boolean Circuits Mitsunori Ogihara . . . . . . . . . . . . . . . . . . . . . . . . . 1817 DNA Assembly and Recombination for Hamiltonian Paths and Binary Words A. Pazos, J. Pazos, and Alfonso R. Patón . . . . . . . . . 1822 Reconstructing Molecular Phylogenetic Tree with Multifurcation by Using Minimum Complexity Principle Fengrong Ren, Hiroshi Tanaka, Toshitsugu Okayama, and Takashi Gojobori . . . . . . . . . . . . . . . . . . . . . . . 1825 A Statistical Mechanical Treatment of Error in the Annealing Biostep of DNA Computation John A. Rose, Russell J. Deaton, Donald R. Franceschetti, Max Garzon, and S. Edward Stevens, Jr. . . . . . . . . . . . . . . . . . . . . 1829 A DNA Implementation of the Max 1s Problem David Wood, Junghuei Chen, Eugene Antipov, Bertrand Lemieux, and Walter Cedeño . . . . . . . . . . 1835 METHODOLOGY, PEDAGOGY AND PHILOSOPHY Populations are Multisets---PLATO Joaquim N. Aparício, Luís Correia, and Fernando Moura­Pires. . . . . . . . . . . . . . . . . . . . 1845 Challenges with Verification, Repeatability, and Meaningful Comparison in Genetic Programming: Gibson's Magic Jason M. Daida, Derrick S. Ampy, Michael Ratanasavetavadhana, Hsiaolei Li, and Omar A. Chaudhri . . . . . . . . . . . . . . . . . . . . . 1851 The Adaptationist Stance and Evolutionary Computation Márk Jelasity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1859 METHODOLOGY, PEDAGOGY AND PHILOSOPHY, POSTER PAPER Generic Evolution Algorithms Programming Library Gabriella Kókai, Zoltán Tóth, and Róbert Ványi . . . . 1867 Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1869 Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1874