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Markov Chain Aggregation for Agent-Based Models
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, o...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
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| Edición: | 1st ed. 2016. |
| Colección: | Understanding Complex Systems,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-24877-6 | ||
| 003 | DE-He213 | ||
| 005 | 20220124132223.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 151221s2016 sz | s |||| 0|eng d | ||
| 020 | |a 9783319248776 |9 978-3-319-24877-6 | ||
| 024 | 7 | |a 10.1007/978-3-319-24877-6 |2 doi | |
| 050 | 4 | |a QC446.15-.3 | |
| 072 | 7 | |a PHJ |2 bicssc | |
| 072 | 7 | |a SCI012000 |2 bisacsh | |
| 072 | 7 | |a PHJ |2 thema | |
| 082 | 0 | 4 | |a 535.2 |2 23 |
| 082 | 0 | 4 | |a 621.3694 |2 23 |
| 100 | 1 | |a Banisch, Sven. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Markov Chain Aggregation for Agent-Based Models |h [electronic resource] / |c by Sven Banisch. |
| 250 | |a 1st ed. 2016. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2016. | |
| 300 | |a XIV, 195 p. 83 illus., 18 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Understanding Complex Systems, |x 1860-0840 | |
| 505 | 0 | |a 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. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Nonlinear Optics. | |
| 650 | 0 | |a System theory. | |
| 650 | 0 | |a Mathematical physics. | |
| 650 | 0 | |a Dynamics. | |
| 650 | 0 | |a Nonlinear theories. | |
| 650 | 1 | 4 | |a Nonlinear Optics. |
| 650 | 2 | 4 | |a Complex Systems. |
| 650 | 2 | 4 | |a Mathematical Methods in Physics. |
| 650 | 2 | 4 | |a Applied Dynamical Systems. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319248752 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319248769 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319796918 |
| 830 | 0 | |a Understanding Complex Systems, |x 1860-0840 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-319-24877-6 |z Texto Completo |
| 912 | |a ZDB-2-PHA | ||
| 912 | |a ZDB-2-SXP | ||
| 950 | |a Physics and Astronomy (SpringerNature-11651) | ||
| 950 | |a Physics and Astronomy (R0) (SpringerNature-43715) | ||