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Understanding Complex Systems

Markov Chain Aggregation for Agent-Based Models

Authors: Banisch, Sven

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  • Introduces and describes a new approach for modelling certain types of complex dynamical systems
  • Self-contained presentation and introductory level
  • Useful as advanced text and as self-study guide
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eBook $69.99
price for USA in USD (gross)
  • ISBN 978-3-319-24877-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
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  • Immediate eBook download after purchase
Hardcover $89.99
price for USA in USD
  • ISBN 978-3-319-24875-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $89.99
price for USA in USD
  • ISBN 978-3-319-79691-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This self-contained text develops a Markov chain approach that makes the rigorous analysis of a class of microscopic models that specify the dynamics of complex systems at the individual level possible. It presents a general framework of aggregation in agent-based and related computational models, one which makes use of lumpability and information theory in order to link the micro and macro levels of observation. The starting point is a microscopic Markov chain description of the dynamical process in complete correspondence with the dynamical behavior of the agent-based model (ABM), which is obtained by considering the set of all possible agent configurations as the state space of a huge Markov chain. An explicit formal representation of a resulting “micro-chain” including microscopic transition rates is derived for a class of models by using the random mapping representation of a Markov process. The type of probability distribution used to implement the stochastic part of the model, which defines the updating rule and governs the dynamics at a Markovian level, plays a crucial part in the analysis of “voter-like” models used in population genetics, evolutionary game theory and social dynamics. The book demonstrates that the problem of aggregation in ABMs - and the lumpability conditions in particular - can be embedded into a more general framework that employs information theory in order to identify different levels and relevant scales in complex dynamical systems

Table of contents (10 chapters)

Table of contents (10 chapters)

Buy this book

eBook $69.99
price for USA in USD (gross)
  • ISBN 978-3-319-24877-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $89.99
price for USA in USD
  • ISBN 978-3-319-24875-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $89.99
price for USA in USD
  • ISBN 978-3-319-79691-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Markov Chain Aggregation for Agent-Based Models
Authors
Series Title
Understanding Complex Systems
Copyright
2016
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-24877-6
DOI
10.1007/978-3-319-24877-6
Hardcover ISBN
978-3-319-24875-2
Softcover ISBN
978-3-319-79691-8
Series ISSN
1860-0832
Edition Number
1
Number of Pages
XIV, 195
Number of Illustrations
65 b/w illustrations, 18 illustrations in colour
Topics