A general mathematical method for predicting spatio-temporal correlations emerging from agent-based models

Show full item record



Permalink

http://hdl.handle.net/10138/322246

Citation

Ovaskainen , O , Somervuo , P & Finkelshtein , D 2020 , ' A general mathematical method for predicting spatio-temporal correlations emerging from agent-based models ' , Journal of the Royal Society Interface , vol. 17 , no. 171 , 20200655 . https://doi.org/10.1098/rsif.2020.0655

Title: A general mathematical method for predicting spatio-temporal correlations emerging from agent-based models
Author: Ovaskainen, Otso; Somervuo, Panu; Finkelshtein, Dmitri
Contributor: University of Helsinki, Organismal and Evolutionary Biology Research Programme
University of Helsinki, Research Centre for Ecological Change
Date: 2020-10-28
Language: eng
Number of pages: 10
Belongs to series: Journal of the Royal Society Interface
ISSN: 1742-5689
URI: http://hdl.handle.net/10138/322246
Abstract: Agent-based models are used to study complex phenomena in many fields of science. While simulating agent-based models is often straightforward, predicting their behaviour mathematically has remained a key challenge. Recently developed mathematical methods allow the prediction of the emerging spatial patterns for a general class of agent-based models, whereas the prediction of spatio-temporal pattern has been thus far achieved only for special cases. We present a general and mathematically rigorous methodology that allows deriving the spatio-temporal correlation structure for a general class of individual-based models. To do so, we define an auxiliary model, in which each agent type of the primary model expands to three types, called the original, the past and the new agents. In this way, the auxiliary model keeps track of both the initial and current state of the primary model, and hence the spatio-temporal correlations of the primary model can be derived from the spatial correlations of the auxiliary model. We illustrate the agreement between analytical predictions and agent-based simulations using two example models from theoretical ecology. In particular, we show that the methodology is able to correctly predict the dynamical behaviour of a host-parasite model that shows spatially localized oscillations.
Subject: agent-based model
marked point process
Markov evolution
theoretical ecology
spatio-temporal correlation
SPATIAL SYNCHRONY
METAPOPULATION DYNAMICS
POPULATION-DYNAMICS
STOCHASTICITY
DISPERSAL
PATTERNS
ROLES
1181 Ecology, evolutionary biology
Rights:


Files in this item

Total number of downloads: Loading...

Files Size Format View
rsif.2020.0655.pdf 874.9Kb PDF View/Open
rsif.2020.0655.pdf 874.9Kb PDF View/Open

This item appears in the following Collection(s)

Show full item record