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Simulators: evolutionary multi-agent system for object recognition in satellite image.

Miu, Hoi Shun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 170-182). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Statement --- p.4 / Chapter 1.2 --- Contributions --- p.5 / Chapter 1.3 --- Thesis Organization --- p.6 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- Multi-agent Systems --- p.8 / Chapter 2.1.1 --- Agent Architectures --- p.9 / Chapter 2.1.2 --- Multi-agent system frameworks --- p.12 / Chapter 2.1.3 --- The Advantages and Disadvantages of Multi-agent Systems --- p.15 / Chapter 2.2 --- Evolutionary Computation --- p.16 / Chapter 2.2.1 --- Genetic Algorithms --- p.17 / Chapter 2.2.2 --- Genetic Programming --- p.18 / Chapter 2.2.3 --- Evolutionary Strategies --- p.19 / Chapter 2.2.4 --- Evolutionary Programming --- p.19 / Chapter 2.3 --- Object Recognition --- p.19 / Chapter 2.3.1 --- Knowledge Representation --- p.20 / Chapter 2.3.2 --- Object Recognition Methods --- p.21 / Chapter 2.4 --- Evolutionary Multi-agent Systems --- p.25 / Chapter 2.4.1 --- Competitive Coevolutionary Agents --- p.26 / Chapter 2.4.2 --- Cooperative Coevolutionary Agents --- p.26 / Chapter 2.4.3 --- Cellular Automata --- p.27 / Chapter 2.4.4 --- Emergent Behavior --- p.28 / Chapter 2.4.5 --- Evolutionary Agents for Image processing and Pattern Recog- nition --- p.29 / Chapter 3 --- System Architecture and Agent Behaviors in SIMULATORS --- p.33 / Chapter 3.1 --- Organization of the System --- p.34 / Chapter 3.1.1 --- General Architecture of Object Recognition System --- p.34 / Chapter 3.1.2 --- Introduction to SIMULATORS --- p.35 / Chapter 3.1.3 --- System Flow of SIMULATORS --- p.37 / Chapter 3.1.4 --- Layered Digital Image Environment --- p.39 / Chapter 3.2 --- Architecture of Autonomous Agents --- p.41 / Chapter 3.2.1 --- Internal Object Model in an Agent --- p.41 / Chapter 3.2.2 --- Current State of an Agent --- p.46 / Chapter 3.2.3 --- Local Information Sensor --- p.46 / Chapter 3.2.4 --- Direction Density Vector --- p.47 / Chapter 3.3 --- Agent Behaviors --- p.48 / Chapter 3.3.1 --- Feature Target Marking --- p.49 / Chapter 3.3.2 --- Reproduction --- p.49 / Chapter 3.3.3 --- Diffusion --- p.52 / Chapter 3.3.4 --- Vanishing --- p.54 / Chapter 3.4 --- Clustering for Autonomous Agent Training --- p.56 / Chapter 3.4.1 --- Introduction --- p.56 / Chapter 3.4.2 --- Creating the Internal Object Model --- p.58 / Chapter 3.5 --- Summary --- p.63 / Chapter 4 --- Evolutionary Algorithms for Multi Agent System --- p.64 / Chapter 4.1 --- Evolutionary Agent Behaviors in SIMULATORS --- p.65 / Chapter 4.1.1 --- Overview --- p.65 / Chapter 4.1.2 --- Evolutionary Autonomous Agents --- p.66 / Chapter 4.1.3 --- Reproduction --- p.68 / Chapter 4.1.4 --- Fitness Function --- p.68 / Chapter 4.1.5 --- Direction Density Vector Propagation --- p.73 / Chapter 4.1.6 --- Mutation --- p.73 / Chapter 4.2 --- Agents Voting Mechanism --- p.74 / Chapter 4.2.1 --- Overview --- p.74 / Chapter 4.2.2 --- Voting for Cooperative Agents --- p.75 / Chapter 4.3 --- Evolutionary Multi Agent Object Recognition --- p.79 / Chapter 4.4 --- Summary --- p.81 / Chapter 5 --- Experimental Results and Applications --- p.82 / Chapter 5.1 --- Experiment Methodology --- p.82 / Chapter 5.1.1 --- Introduction to Fung Shui Woodland --- p.83 / Chapter 5.1.2 --- Testing Images --- p.83 / Chapter 5.1.3 --- Creating Internal Object Model --- p.85 / Chapter 5.1.4 --- Experiment Parameters --- p.86 / Chapter 5.2 --- Experimental Results of Fung Shui Woodland Recognition --- p.92 / Chapter 5.2.1 --- Experiment 1: artificial0l --- p.92 / Chapter 5.2.2 --- Experiment 2: artificial0l´ؤnoise --- p.92 / Chapter 5.2.3 --- Experiment 3: artificial02 --- p.93 / Chapter 5.2.4 --- Experiment 4: FungShui0l --- p.93 / Chapter 5.2.5 --- Experiment 5: FungShui0l´ؤnoise --- p.94 / Chapter 5.2.6 --- Experiments 6 to 11: FungShui02 to FungShui07 --- p.94 / Chapter 5.3 --- Discussion --- p.119 / Chapter 5.4 --- An Example of Eyes Detection --- p.124 / Chapter 5.4.1 --- Result of the Eyes Detection --- p.128 / Chapter 5.5 --- Summary --- p.132 / Chapter 6 --- Conclusion --- p.133 / Chapter 6.1 --- Summary --- p.133 / Chapter 6.2 --- Future Work --- p.136 / Chapter A --- The Figures in the Experiments --- p.138

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324785
Date January 2004
ContributorsMiu, Hoi Shun., 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, xvi, 182 leaves : ill. (some col.) ; 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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