Detection and reification of emerging dynamical ecosystems from interaction networks

Guillaume Prévost (1) , Cyrille Bertelle (1)

1 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes

In this paper, we present an hybrid ecosystem modeling based on emerging computation from interaction networks. Initially based on an individual-based modeling (IBM) simulation, we propose an automatic computation to detect predator-preys systems. After their detection, these systems are replaced by a differential system during the simulation. In this way, we can change the description level and improve both the computation time and the whole system analysis by detecting some emergent organizations. The description modification between IBM representation to differential one needs to identify the global coefficients of these differential equations. Due to the complexity of relations between these two kinds of representations, a genetic algorithm is proposed to solve this identification.

Mots clés: ontology; Complex systems; ecosystems; interaction networks; emerging systems; non-linear differential systems; genetic algorithms; ontology.

Domaines: Adaptation et Systèmes auto-organisés [nlin.AO]; Intelligence artificielle [cs.AI]

Guillaume Prévost, Cyrille Bertelle. Detection and reification of emerging dynamical ecosystems from interaction networks. Cyrille Bertelle and Gérard H.E. Duchamp and Hakima Kadri-Dahmani. Complex Systems and Self-organization Modelling, Springer-Verlag, pp.139-161, 2009, Understanding Complex Systems, ⟨10.1007/978-3-540-88073⟩. ⟨hal-00430554⟩