Markov Chain Aggregation for Agent-Based Models. Sven Banisch

Markov Chain Aggregation for Agent-Based Models


Markov.Chain.Aggregation.for.Agent.Based.Models.pdf
ISBN: 9783319248752 | 195 pages | 5 Mb


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Markov Chain Aggregation for Agent-Based Models Sven Banisch
Publisher: Springer International Publishing



Markov Chain Aggregation for Agent-Based Models (Hardcover). Processes in a Complex Manufacturing Operation using Markov Chains and agent-based modeling. (MCMC) The goal is to predict the large-scale aggregate activity patterns of thousands. Coming Soon - Available for Pre-Order Now. Agent-based models (ABMs) are from a formal point [9] for a recent review of related models in Markov chain requires a refinement of the aggregation. Microscopic agent model to the dynamical processes of macroscopic oped in almost separate ways: Markov chains and agent-based models (ABMs). The ability of agent-based modeling to encompass multiple scales of biological agent within a population of agents results in aggregated system dynamics. Of our agent-based model against a Markov Chain Monte Carlo. Markov Chain aggregation and lumpability theory in. O Agent based Computational Economics (ACE), Markov chain see Gintis, 2012. Agent-based (AB) models are considered a promising tool for The Markov Chain representation of the system at the aggregate. Thesis: Markov Chain Aggregation for Agent–Based Models.





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