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A probabilistic cooperative-competitive hierarchical search model.

by Wong Yin Bun, Terence. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 99-104). / Abstract also in Chinese. / List of Figures --- p.ix / List of Tables --- p.xi / Chapter I --- Preliminary --- p.1 / Chapter 1 --- Introduction --- p.2 / Chapter 1.1 --- Thesis themes --- p.4 / Chapter 1.1.1 --- Dynamical view of landscape --- p.4 / Chapter 1.1.2 --- Bottom-up self-feedback algorithm with memory --- p.4 / Chapter 1.1.3 --- Cooperation and competition --- p.5 / Chapter 1.1.4 --- Contributions to genetic algorithms --- p.5 / Chapter 1.2 --- Thesis outline --- p.5 / Chapter 1.3 --- Contribution at a glance --- p.6 / Chapter 1.3.1 --- Problem --- p.6 / Chapter 1.3.2 --- Approach --- p.7 / Chapter 1.3.3 --- Contributions --- p.7 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- Iterative stochastic searching algorithms --- p.8 / Chapter 2.1.1 --- The algorithm --- p.8 / Chapter 2.1.2 --- Stochasticity --- p.10 / Chapter 2.2 --- Fitness landscapes and its relation to neighborhood --- p.12 / Chapter 2.2.1 --- Direct searching --- p.12 / Chapter 2.2.2 --- Exploration and exploitation --- p.12 / Chapter 2.2.3 --- Fitness landscapes --- p.13 / Chapter 2.2.4 --- Neighborhood --- p.16 / Chapter 2.3 --- Species formation methods --- p.17 / Chapter 2.3.1 --- Crowding methods --- p.17 / Chapter 2.3.2 --- Deterministic crowding --- p.18 / Chapter 2.3.3 --- Sharing method --- p.18 / Chapter 2.3.4 --- Dynamic niching --- p.19 / Chapter 2.4 --- Summary --- p.21 / Chapter II --- Probabilistic Binary Hierarchical Search --- p.22 / Chapter 3 --- The basic algorithm --- p.23 / Chapter 3.1 --- Introduction --- p.23 / Chapter 3.2 --- Search space reduction with binary hierarchy --- p.25 / Chapter 3.3 --- Search space modeling --- p.26 / Chapter 3.4 --- The information processing cycle --- p.29 / Chapter 3.4.1 --- Local searching agents --- p.29 / Chapter 3.4.2 --- Global environment --- p.30 / Chapter 3.4.3 --- Cooperative refinement and feedback --- p.33 / Chapter 3.5 --- Enhancement features --- p.34 / Chapter 3.5.1 --- Fitness scaling --- p.34 / Chapter 3.5.2 --- Elitism --- p.35 / Chapter 3.6 --- Illustration of the algorithm behavior --- p.36 / Chapter 3.6.1 --- Test problem --- p.36 / Chapter 3.6.2 --- Performance study --- p.38 / Chapter 3.6.3 --- Benchmark tests --- p.45 / Chapter 3.7 --- Discussion and analysis --- p.45 / Chapter 3.7.1 --- Hierarchy of partitions --- p.45 / Chapter 3.7.2 --- Availability of global information --- p.47 / Chapter 3.7.3 --- Adaptation --- p.47 / Chapter 3.8 --- Summary --- p.48 / Chapter III --- Cooperation and Competition --- p.50 / Chapter 4 --- High-dimensionality --- p.51 / Chapter 4.1 --- Introduction --- p.51 / Chapter 4.1.1 --- The challenge of high-dimensionality --- p.51 / Chapter 4.1.2 --- Cooperation - A solution to high-dimensionality --- p.52 / Chapter 4.2 --- Probabilistic Cooperative Binary Hierarchical Search --- p.52 / Chapter 4.2.1 --- Decoupling --- p.52 / Chapter 4.2.2 --- Cooperative fitness --- p.53 / Chapter 4.2.3 --- The cooperative model --- p.54 / Chapter 4.3 --- Empirical performance study --- p.56 / Chapter 4.3.1 --- pBHS versus pcBHS --- p.56 / Chapter 4.3.2 --- Scaling behavior of pcBHS --- p.60 / Chapter 4.3.3 --- Benchmark test --- p.62 / Chapter 4.4 --- Summary --- p.63 / Chapter 5 --- Deception --- p.65 / Chapter 5.1 --- Introduction --- p.65 / Chapter 5.1.1 --- The challenge of deceptiveness --- p.65 / Chapter 5.1.2 --- Competition: A solution to deception --- p.67 / Chapter 5.2 --- Probabilistic cooperative-competitive binary hierarchical search --- p.67 / Chapter 5.2.1 --- Overview --- p.68 / Chapter 5.2.2 --- The cooperative-competitive model --- p.68 / Chapter 5.3 --- Empirical performance study --- p.70 / Chapter 5.3.1 --- Goldberg's deceptive function --- p.70 / Chapter 5.3.2 --- "Shekel family - S5, S7, and S10" --- p.73 / Chapter 5.4 --- Summary --- p.74 / Chapter IV --- Finale --- p.78 / Chapter 6 --- A new genetic operator --- p.79 / Chapter 6.1 --- Introduction --- p.79 / Chapter 6.2 --- Variants of the integration --- p.80 / Chapter 6.2.1 --- Fixed-fraction-of-all --- p.83 / Chapter 6.2.2 --- Fixed-fraction-of-best --- p.83 / Chapter 6.2.3 --- Best-from-both --- p.84 / Chapter 6.3 --- Empricial performance study --- p.84 / Chapter 6.4 --- Summary --- p.88 / Chapter 7 --- Conclusion and Future work --- p.89 / Chapter A --- The pBHS Algorithm --- p.91 / Chapter A.1 --- Overview --- p.91 / Chapter A.2 --- Details --- p.91 / Chapter B --- Test problems --- p.96 / Bibliography --- p.99

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_322249
Date January 1998
ContributorsWong, Yin Bun Terence., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, xi, 104 leaves : ill. ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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