Genetic Programming (eBook, PDF)

Second European Workshop, EuroGP'99, Göteborg, Sweden, May 26-27, 1999, Proceedings
Redaktion: Poli, Riccardo; Fogarty, Terence C.; Langdon, William B.; Nordin, Peter

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the Second European Workshop on Genetic Programming, EuroPG '99, held in Göteborg, Sweden in May 1999. The 12 revised full papers and 11 posters presented have been carefully reviewed and selected for inclusion in the book. All the relevant aspects of genetic programming are addressed ranging from traditional and foundational issues to applications in a variety of fields.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 290
• Erscheinungstermin: 31. Juli 2003
• Englisch
• ISBN-13: 9783540488859
• Artikelnr.: 53135336

Inhaltsangabe

Representations.- Boolean Functions Fitness Spaces.- Meta-Evolution in Graph GP.- Busy Beaver - The Influence of Representation.- Algorithms and Operators.- Mutation in Genetic Programming: A Preliminary Study.- A Comparison of Darwinian and Lamarckian Inheritance Schemes.- Sub-machine-code GP: New Results and Extensions.- Evolving Multi-line Compilable C Programs.- Applications.- Genetic Programming as a Darwinian Invention Machine.- Genetic Programming of a Goal-Keeper Control Strategy for the RoboCup Middle Size Competition.- Genetic Programming Discovers Efficient Learning Rules for the Hidden and Output Layers of Feedforward Neural Networks.- Evolution of Ship Detectors for Satellite SAR Imagery.- Automatic Generation of Affine IFS and Strongly Typed Genetic Programming.- Posters.- Reactive and Memory-Based Genetic Programming for Robot Control.- Distributed and Persistent Evolutionary Algorithms: A Design Pattern.- Evolving an Environment Model for Robot Localization.- Adapting the Fitness Function in GP for Data Mining.- Evolving Fuzzy Rule Based Classifiers with GA-P: A Grammatical Approach.- Evolving Neural Network Structures by Means of Genetic Programming.- Genetic Reasoning: Evolutionary Induction of Mathematical Proofs.- How to Invent Functions.- Automatic Parallelization of Arbitrary Programs.- Evolving Controllers for Autonomous Agents Using Genetically Programmed Networks.- Concurrent Genetic Programming, Tartarus and Dancing Agents.