Phylogeny and Taxonomic Revision of Tylenchidae with Emphasis on the Genus Cephalenchus (Tylenchina:

مرکز و کتابخانه مطالعات اسلامی به زبان های اروپایی

منو

" Phylogeny and Taxonomic Revision of Tylenchidae with Emphasis on the Genus Cephalenchus (Tylenchina: "
Pereira, Tiago Jose Baldwin, James G

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.