This paper provides an algorithmic pipeline for studying the intrinsic structure of a finite discrete dynamical system (DDS) modelling an evolving phenomenon. Here, by intrinsic structure we mean, regarding the dynamics of the DDS under observation, the feature of resulting from the ‘cooperation’ of the dynamics of two or more smaller DDS. The intrinsic structure is described by an equation over DDS which represents a hypothesis over the phenomenon under observation. The pipeline allows solving such an equation, i.e., validating the hypothesis over the phenomenon, as far the asymptotic behaviour and the number of states of the DDS under observation are concerned. The results are about the soundness and completeness of the pipeline and they are obtained by exploiting the algebraic setting for DDS introduced in Dennunzio et al. (2018).

Alberto Dennunzio, E.F. (2023). An algorithmic pipeline for solving equations over discrete dynamical systems modelling hypothesis on real phenomena. JOURNAL OF COMPUTATIONAL SCIENCE, 66, 1-13 [10.1016/j.jocs.2022.101932].

An algorithmic pipeline for solving equations over discrete dynamical systems modelling hypothesis on real phenomena

Luciano Margara;
2023

Abstract

This paper provides an algorithmic pipeline for studying the intrinsic structure of a finite discrete dynamical system (DDS) modelling an evolving phenomenon. Here, by intrinsic structure we mean, regarding the dynamics of the DDS under observation, the feature of resulting from the ‘cooperation’ of the dynamics of two or more smaller DDS. The intrinsic structure is described by an equation over DDS which represents a hypothesis over the phenomenon under observation. The pipeline allows solving such an equation, i.e., validating the hypothesis over the phenomenon, as far the asymptotic behaviour and the number of states of the DDS under observation are concerned. The results are about the soundness and completeness of the pipeline and they are obtained by exploiting the algebraic setting for DDS introduced in Dennunzio et al. (2018).
2023
Alberto Dennunzio, E.F. (2023). An algorithmic pipeline for solving equations over discrete dynamical systems modelling hypothesis on real phenomena. JOURNAL OF COMPUTATIONAL SCIENCE, 66, 1-13 [10.1016/j.jocs.2022.101932].
Alberto Dennunzio, Enrico Formenti, Luciano Margara, Sara Riva
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/911417
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