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Modeling complex processes through n...
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Klüver, Christina.
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Modeling complex processes through nature-analogous methods = artificial intelligence and artificial life /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Modeling complex processes through nature-analogous methods/ by Christina Klüver, Jürgen Klüver, Jörn Schmidt.
其他題名:
artificial intelligence and artificial life /
作者:
Klüver, Christina.
其他作者:
Klüver, Jürgen.
出版者:
Wiesbaden :Springer Fachmedien Wiesbaden : : 2025.,
面頁冊數:
xii, 366 p. :ill. (some col.), digital ;24 cm.
內容註:
Bottom-up models, complex systems, and nature-analogous methods of AI and AL -- Self-organizing systems: cellular automata, Boolean networks, and neighborhood generating algorithms -- The modeling of adaptive processes through evolutionary algorithms -- Modeling learning systems through neural networks -- Modeling the imprecise: fuzzy set theory and fuzzy logic -- Hybridizations of the basic models -- Summary and perspectives.
Contained By:
Springer Nature eBook
標題:
Computational intelligence. -
電子資源:
https://doi.org/10.1007/978-3-658-46510-0
ISBN:
9783658465100
Modeling complex processes through nature-analogous methods = artificial intelligence and artificial life /
Klüver, Christina.
Modeling complex processes through nature-analogous methods
artificial intelligence and artificial life /[electronic resource] :by Christina Klüver, Jürgen Klüver, Jörn Schmidt. - Wiesbaden :Springer Fachmedien Wiesbaden :2025. - xii, 366 p. :ill. (some col.), digital ;24 cm.
Bottom-up models, complex systems, and nature-analogous methods of AI and AL -- Self-organizing systems: cellular automata, Boolean networks, and neighborhood generating algorithms -- The modeling of adaptive processes through evolutionary algorithms -- Modeling learning systems through neural networks -- Modeling the imprecise: fuzzy set theory and fuzzy logic -- Hybridizations of the basic models -- Summary and perspectives.
This book is an introduction to nature-analogous techniques and related formal methods. For each technique, application examples are provided. It covers cellular automata and Boolean networks, evolutionary algorithms, as well as simulated annealing, fuzzy methods, neural networks, and finally hybrid systems, i.e., combinations of various techniques. Based on the theory of complex dynamic systems, theoretical foundations are also presented, and the similarities of these seemingly very heterogeneous techniques are pointed out. The edition has been revised and expanded with current trends such as ChatGPT. Content Bottom-up models, complex systems, and nature-analogous methods of AI and AL Self-organizing systems: cellular automata, Boolean networks, and neighborhood generating algorithms The modeling of adaptive processes through evolutionary algorithms Modeling learning systems through neural networks Modeling the imprecise: fuzzy set theory and fuzzy logic Hybridizations of the basic models Summary and perspectives Target Audience Students, educators, and practitioners interested in new modeling with methods of Artificial Intelligence and Artificial Life for their professional activities. Authors PD Dr. Christina Klüver, Prof. Dr. Jürgen Klüver, and Dr. Jörn Schmidt form the research group COBASC (Computer Based Analysis of Social Complexity). They developed numerous computer programs for the simulation and analysis of complex processes. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.
ISBN: 9783658465100
Standard No.: 10.1007/978-3-658-46510-0doiSubjects--Topical Terms:
595739
Computational intelligence.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Modeling complex processes through nature-analogous methods = artificial intelligence and artificial life /
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Bottom-up models, complex systems, and nature-analogous methods of AI and AL -- Self-organizing systems: cellular automata, Boolean networks, and neighborhood generating algorithms -- The modeling of adaptive processes through evolutionary algorithms -- Modeling learning systems through neural networks -- Modeling the imprecise: fuzzy set theory and fuzzy logic -- Hybridizations of the basic models -- Summary and perspectives.
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