Overview
- Nominated as an outstanding PhD thesis from the University of Sydney
- This thesis develops the first complete framework to quantify the information dynamics of distributed computation, with possible application to biological and bio-inspired systems
- Unique in blending theoretical contributions (e.g. fundamental insights into computation in cellular automata) with practical results (e.g. in computational neuroscience)
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Theses (Springer Theses)
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About this book
The nature of distributed computation in complex systems has often been described in terms of memory, communication and processing. This thesis presents a complete information-theoretic framework to quantify these operations on information (i.e. information storage, transfer and modification), and in particular their dynamics in space and time. The framework is applied to cellular automata, and delivers important insights into the fundamental nature of distributed computation and the dynamics of complex systems (e.g. that gliders are dominant information transfer agents). Applications to several important network models, including random Boolean networks, suggest that the capability for information storage and coherent transfer are maximised near the critical regime in certain order-chaos phase transitions. Further applications to study and design information structure in the contexts of computational neuroscience and guided self-organisation underline the practical utility of the techniques presented here.
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: The Local Information Dynamics of Distributed Computation in Complex Systems
Authors: Joseph T. Lizier
Series Title: Springer Theses
DOI: https://doi.org/10.1007/978-3-642-32952-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-32951-7Published: 06 November 2012
Softcover ISBN: 978-3-642-43819-6Published: 14 December 2014
eBook ISBN: 978-3-642-32952-4Published: 06 November 2012
Series ISSN: 2190-5053
Series E-ISSN: 2190-5061
Edition Number: 1
Number of Pages: XXIV, 236
Topics: Complexity, Coding and Information Theory, Artificial Intelligence, Computational Biology/Bioinformatics