Abstract
In this note we present a method to compute approximate descriptions of a class of stochastic systems. For the method to apply, the system must be presented as a Markov chain on a state space consisting in graphs or graph-like objects, and jumps must be described by transformations which follow a finite set of local rules.
This research was sponsored by the European Research Council (ERC) under the grants 587327 “DOPPLER” and 320823 “RULE”.
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References
Durrett, R., Gleeson, J.P., Lloyd, A.L., Mucha, P.J., Shi, F., Sivakoff, D., Socolar, J.E., Varghese, C.: Graph fission in an evolving voter model. Proceedings of the National Academy of Sciences 109(10), 3682–3687 (2012)
Gleeson, J.P.: High-accuracy approximation of binary-state dynamics on networks. Physical Review Letters 107(6), 068701 (2011)
Harmer, R., Danos, V., Feret, J., Krivine, J., Fontana, W.: Intrinsic information carriers in combinatorial dynamical systems. Chaos 20(3) (2010)
Norris, J.R.: Markov chains. Cambridge series in statistical and probabilistic mathematics. Cambridge University Press (1998)
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Danos, V., Heindel, T., Honorato-Zimmer, R., Stucki, S. (2014). Approximations for Stochastic Graph Rewriting. In: Merz, S., Pang, J. (eds) Formal Methods and Software Engineering. ICFEM 2014. Lecture Notes in Computer Science, vol 8829. Springer, Cham. https://doi.org/10.1007/978-3-319-11737-9_1
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DOI: https://doi.org/10.1007/978-3-319-11737-9_1
Publisher Name: Springer, Cham
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