We present a scalable and dimension‐insensitive simulation algorithm in which dimensionality is taken care of by not enumerating the agents' configurations; scalability is obtained by storing all potential events. This results in a simulation event cost which is purely logarithmic in the static measure of the rule set (number and size of rules) and opens the way for an implementation which can handle systems which are both large and high‐dimensional.
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Research Article| December 26 2007
Jean Krivine; An Exact and Scalable Stochastic Simulation Algorithm.. AIP Conf. Proc. 26 December 2007; 963 (2): 638–641. https://doi.org/10.1063/1.2836164
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