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Titlebook: Genetic and Evolutionary Computation - GECCO 2003; Genetic and Evolutio Erick Cantú-Paz,James A. Foster,Julian Miller Conference proceeding

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發(fā)表于 2025-3-21 19:30:25 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Genetic and Evolutionary Computation - GECCO 2003
副標(biāo)題Genetic and Evolutio
編輯Erick Cantú-Paz,James A. Foster,Julian Miller
視頻videohttp://file.papertrans.cn/383/382651/382651.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Genetic and Evolutionary Computation - GECCO 2003; Genetic and Evolutio Erick Cantú-Paz,James A. Foster,Julian Miller Conference proceeding
出版日期Conference proceedings 2003
關(guān)鍵詞agents; algorithm; algorithms; evolution; evolutionary computation; genetic algorithm; genetic algorithms;
版次1
doihttps://doi.org/10.1007/3-540-45105-6
isbn_softcover978-3-540-40602-0
isbn_ebook978-3-540-45105-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2003
The information of publication is updating

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發(fā)表于 2025-3-21 23:12:52 | 只看該作者
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A Periodization of South African History, 3D environment, are based on a multi-agent model. Natural oaks and beeches develop two different strategies to exploit light. The model presented in this paper uses these properties during the plant growth. Most of the results are close to those obtained in natural conditions on long-term evolution of forests.
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Clustering and Dynamic Data Visualization with Artificial Flying Insectng insects that move together in complex manner with simple local rules. Each insect represents one datum. The insect moves aim at creating homogeneous groups of data that evolve together in a 2D environment in order to help the domain expert to understand the underlying class structure of the data set.
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發(fā)表于 2025-3-22 20:09:18 | 只看該作者
Ant Colony Programming for Approximation Problemsdea of ant colony programming in which instead of a genetic algorithm an ant colony algorithm is applied to search for the program. The test results demonstrate that the proposed idea can be used with success to solve the approximation problems.
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Long-Term Competition for Light in Plant Simulation 3D environment, are based on a multi-agent model. Natural oaks and beeches develop two different strategies to exploit light. The model presented in this paper uses these properties during the plant growth. Most of the results are close to those obtained in natural conditions on long-term evolution of forests.
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Pick und andere fokale Hirnatrophienopulation of digital organisms (self-replicating computer programs) that evolve subject to natural selection, mutation, and drift. We compare the performance of neighbor-joining and maximum parsimony algorithms on these Avida populations to the performance of the same algorithms on randomly generate
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