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Titlebook: Simulated Evolution and Learning; 7th International Co Xiaodong Li,Michael Kirley,Yuhui Shi Conference proceedings 2008 Springer-Verlag Ber

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发表于 2025-3-21 18:04:19 | 显示全部楼层 |阅读模式
书目名称Simulated Evolution and Learning
副标题7th International Co
编辑Xiaodong Li,Michael Kirley,Yuhui Shi
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Simulated Evolution and Learning; 7th International Co Xiaodong Li,Michael Kirley,Yuhui Shi Conference proceedings 2008 Springer-Verlag Ber
描述This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning,held December 7–10, 2008, in Melbourne, Australia. SEAL is a prestigious international conference series in evolutionary computation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), Busan, Korea (2004), and Hefei, China (2006). SEAL 2008 received 140 paper submissions from more than 30 countries. After a rigorous peer-review process involving at least 3 reviews for each paper (i.e., over 420 reviews in total), the best 65 papers were selected to be presented at the conference and included in this volume, resulting in an acceptance rate of about 46%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world.
出版日期Conference proceedings 2008
关键词Alife; Scheduling; adaptive systems; algorithms; ant colonies; ant colony optimization; ants; artificial li
版次1
doihttps://doi.org/10.1007/978-3-540-89694-4
isbn_softcover978-3-540-89693-7
isbn_ebook978-3-540-89694-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2008
The information of publication is updating

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Md. Rafiul Hassan,M. Maruf Hossain,C. K. Karmakar,Michael Kirley
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Andrea Arcuri,David Robert White,John Clark,Xin Yao
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Breaking the Synaptic Dogma: Evolving a Neuro-inspired Developmental Networkhe seven programs are run, the neurons, dendrites, axons and synapses can increase or decrease in number and change in interaction with an external environment. Our aim is to show that it is possible to evolve programs that allow a network to learn through experience (i.e. encode the . to learn). We
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Genetically Evolved Fuzzy Rule-Based Classifiers and Application to Automotive Classificatione imprecise and the fuzzy classifier itself has not enough degrees of freedom to construct a suitable boundary. Conversely, when decision boundaries are clear, the advantage of type-2 framework may not be significant anymore. In any case, the performance of a type-2 fuzzy classifier is at least comp
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Conference proceedings 2008tionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world.
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