Abstract
We analyze the dynamics of agent-based models (ABMs) from a Markovian perspective and derive explicit statements about the possibility of linking a microscopic agent model to the dynamical processes of macroscopic observables that are useful for a precise understanding of the model dynamics. In this way the dynamics of collective variables may be studied, and a description of macro dynamics as emergent properties of micro dynamics, in particular during transient times, is possible.
This work has benefited from financial support from the Fundação para a Ciência e a Tecnologia (FCT), under the 13 Multi-annual Funding Project of UECE, ISEG, Technical University of Lisbon. Financial support of the German Federal Ministry of Education and Research (BMBF) through the project Linguistic Networks is also gratefully acknowledged (http://project.linguistic-networks.net).
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Banisch, S., Lima, R., Araújo, T. (2013). Aggregation and Emergence in Agent-Based Models: A Markov Chain Approach. In: Gilbert, T., Kirkilionis, M., Nicolis, G. (eds) Proceedings of the European Conference on Complex Systems 2012. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-00395-5_1
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DOI: https://doi.org/10.1007/978-3-319-00395-5_1
Publisher Name: Springer, Cham
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