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"
Mandatory and voluntary disclosures in GCC listed firms
"
Boshnak, H.
Document Type
:
BL
Record Number
:
649969
Doc. No
:
dltt
Main Entry
:
Banisch, Sven
Title & Author
:
Markov chain aggregation for agent-based models /\ Sven Banisch
Series Statement
:
Understanding complex systems,
:
Springer complexity
Page. NO
:
1 online resource (xiv, 195 pages) :: illustrations (some color).
ISBN
:
9783319248776
:
: 3319248774
:
9783319248752
:
: 3319248758 (print)
:
: 9783319248752 (print)
Bibliographies/Indexes
:
Includes bibliographical references
Contents
:
Introduction -- Background and Concepts -- Agent-based Models as Markov Chains -- The Voter Model with Homogeneous Mixing -- From Network Symmetries to Markov Projections -- Application to the Contrarian Voter Model -- Information-Theoretic Measures for the Non-Markovian Case -- Overlapping Versus Non-Overlapping Generations -- Aggretion and Emergence: A Synthesis -- Conclusion
Abstract
:
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 ĺlmicro-chainĺl 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 ĺlvoter-likeĺl 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
Subject
:
Markov processes.
Subject
:
Multiagent systems.
Dewey Classification
:
519.2/33
LC Classification
:
QA274.7
Added Entry
:
Ohio Library and Information Network.
https://lib.clisel.com/site/catalogue/832493
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TLets714998_81838.pdf
TLets714998.pdf
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