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Titlebook: Computational Evolution of Neural and Morphological Development; Towards Evolutionary Yaochu Jin Book 2023 The Editor(s) (if applicable) an

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發(fā)表于 2025-3-21 20:02:39 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computational Evolution of Neural and Morphological Development
副標題Towards Evolutionary
編輯Yaochu Jin
視頻videohttp://file.papertrans.cn/233/232280/232280.mp4
概述Integrates evolution, learning and development in a united computing framework.Includes detailed examples of evolving genetic networks, brain-body coevolution, and self-organizing swarm robots.Introdu
叢書名稱Natural Computing Series
圖書封面Titlebook: Computational Evolution of Neural and Morphological Development; Towards Evolutionary Yaochu Jin Book 2023 The Editor(s) (if applicable) an
描述.This book provides a basic yet unified overview of theory and methodologies for evolutionary developmental systems. Based on the author’s extensive research into the synergies between various approaches to artificial intelligence including evolutionary computation, artificial neural networks, and systems biology, it also examines the inherent links between biological intelligence and artificial intelligence.?..The book begins with an introduction to computational algorithms used to understand and simulate biological evolution and development, including evolutionary algorithms, gene regulatory network models, multi-cellular models for neural and morphological development, and computational models of neural plasticity. Chap.?2 discusses important properties of biological gene regulatory systems, including network motifs, network connectivity, robustness and evolvability. Going a step further, Chap.?3 presents methods for synthesizing regulatory motifs from scratch and creating more complex regulatory dynamics by combining basic regulatory motifs using evolutionary algorithms. Multi-cellular growth models, which can be used to simulate either neural or morphological development, are
出版日期Book 2023
關(guān)鍵詞Evolutionary Developmental Systems; Evolution; Gene Regulatory Networks; Morphogenesis; Self-Organizatio
版次1
doihttps://doi.org/10.1007/978-981-99-1854-6
isbn_softcover978-981-99-1856-0
isbn_ebook978-981-99-1854-6Series ISSN 1619-7127 Series E-ISSN 2627-6461
issn_series 1619-7127
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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發(fā)表于 2025-3-21 22:15:56 | 只看該作者
Die Stiftungslandschaft in Deutschland,real-world example in which a biological gene regulatory pathway governing the production of antibiotics in streptomyces is reconstructed based on gene expression data. This example demonstrates that evolutionary algorithms are competitive in reverse-engineered biological networks containing over 900 genes.
板凳
發(fā)表于 2025-3-22 01:22:51 | 只看該作者
Die Stiftungsidee und ihre Umsetzung,cture using plasticity in a spiking neural network-based reservoir model. Liquid state machines with self-organized reservoir and multiple sub-reservoir are evolved. Finally, local synaptic and intrinsic rules are evolved to regulate the structure of echo-state-networks for better performing regression and classification tasks.
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Evolution of Neural Development,cture using plasticity in a spiking neural network-based reservoir model. Liquid state machines with self-organized reservoir and multiple sub-reservoir are evolved. Finally, local synaptic and intrinsic rules are evolved to regulate the structure of echo-state-networks for better performing regression and classification tasks.
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Computational Models of Evolution and Development,ating morphological and neural development governed by gene regulatory networks and cellular interactions are given, providing the foundation models for evolving neural and morphological development. Finally, computational models of activity-dependent neural plasticity, including the BCM rule and spike-timing-dependent plasticity rule are given.
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