Alexander Gebharter
Ludwig Maximilians Universität, München
Causal Bayes nets (CBNs) can be used to model causal relationships up to whole mechanisms. Though modelling mechanisms with CBNs comes with many advantages, CBNs might fail to adequately represent some biological mechanisms because—as Kaiser (2016) pointed out—they have problems with capturing relevant spatial and structural information. In this paper we propose a hybrid approach for modelling mechanisms that combines CBNs and cellular automata. Our approach can incorporate spatial and structural information while, at the same time, it comes with all the merits of a CBN representation of mechanisms.
Keywords philosophy of science  philosophy of biology  systems biology  causation  modeling  simulation  cellular automata  Bayesian networks  mechanisms
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Reprint years 2018
DOI 10.1093/bjps/axy049
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References found in this work BETA

Explaining the Brain.Carl F. Craver - 2009 - Oxford University Press.
Thinking About Mechanisms.Peter Machamer, Lindley Darden & Carl F. Craver - 2000 - Philosophy of Science 67 (1):1-25.
Explanation: A Mechanist Alternative.William Bechtel & Adele Abrahamsen - 2005 - Studies in History and Philosophy of Biological and Biomedical Sciences 36 (2):421-441.

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