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| book details |
Markov Chain Aggregation for Agent-Based Models
By (author) Sven Banisch
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normal price: R 2 466.95
Price: R 2 219.95
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| book description |
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
| product details |
Normally shipped |
Publisher | Springer International Publishing AG
Published date | 5 Jan 2016
Language |
Format | Hardback
Pages | 195
Dimensions | 235 x 155 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-3-3192-4875-2
Readership Age |
BISAC | mathematics / linear programming
| other options |
Normally shipped |
Readership Age |
Normal Price | R 3 268.95
Price | R 2 941.95
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