Abstract
In this paper we present two approaches, namely correlative and static causality, to study cause-effect relationships in reaction models and we propose a framework which integrates them in order to study causality by means of transition P systems. The proposed framework is based on the fact that statistical analysis can be used to building up a membrane model which can be used to analyze causality relationships in terms of multisets of objects and rules in presence of non-determinism and parallelism. We prove that the P system which is defined by means of correlation analysis provides a correspondence between the static and correlative notions of causality.
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Pagliarini, R., Agrigoroaiei, O., Ciobanu, G., Manca, V. (2013). An Analysis of Correlative and Static Causality in P Systems. In: Csuhaj-Varjú, E., Gheorghe, M., Rozenberg, G., Salomaa, A., Vaszil, G. (eds) Membrane Computing. CMC 2012. Lecture Notes in Computer Science, vol 7762. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36751-9_22
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DOI: https://doi.org/10.1007/978-3-642-36751-9_22
Publisher Name: Springer, Berlin, Heidelberg
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