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Markov Chain Aggregation for Agent-Based Models

by Sven Banisch
Save 35% Save 35%
Current price ₹5,509.00
Original price ₹8,474.00
Original price ₹8,474.00
Original price ₹8,474.00
(-35%)
₹5,509.00
Current price ₹5,509.00

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Book cover type: Paperback
  • ISBN13: 9783319796918
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 195
  • Original Price: EUR 74.99
  • Language: English
  • Edition: Softcover Repri
  • Item Weight: 309 grams
  • BISAC Subject(s): Engineering (General), Chaotic Behavior in Systems, and Applied

From the Back Cover
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

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