Overview
- Presents a concise introduction to morphogenetic computing
- Introduces a fundamental new approach to computation by which you can move from uncertainty, inconsistency, and imprecision to a more logical stable and consistent situation
- Shows that global and local relations, defects in crystal non-Euclidean geometry databases with source and sink, genetic algorithms, and neural networks all become more stable and efficient when using morphogenetic computing
- Includes supplementary material: sn.pub/extras
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 703)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book offers a concise introduction to morphogenetic computing, showing that its use makes global and local relations, defects in crystal non-Euclidean geometry databases with source and sink, genetic algorithms, and neural networks more stable and efficient. It also presents applications to database, language, nanotechnology with defects, biological genetic structure, electrical circuit, and big data structure. In Turing machines, input and output states form a system – when the system is in one state, the input is transformed into output. This computation is always deterministic and without any possible contradiction or defects. In natural computation there are defects and contradictions that have to be solved to give a coherent and effective computation. The new computation generates the morphology of the system that assumes different forms in time. Genetic process is the prototype of the morphogenetic computing. At the Boolean logic truth value, we substitute a set of truth(active sets) values with possible contradictions. The value of a proposition is a set of true and false values. The aim of morphogenetic computing is to use and solve the contradictions in order to transform systems to allow classical computation.
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Authors and Affiliations
Bibliographic Information
Book Title: Introduction to Morphogenetic Computing
Authors: Germano Resconi, Xiaolin Xu, Guanglin Xu
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-57615-2
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-57614-5Published: 19 May 2017
Softcover ISBN: 978-3-319-86208-8Published: 28 July 2018
eBook ISBN: 978-3-319-57615-2Published: 09 May 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: IX, 172
Number of Illustrations: 145 b/w illustrations
Topics: Computational Intelligence, Artificial Intelligence, Mathematical Applications in Computer Science