Bonté Bruno

Irstea − Lisc
9 avenue Blaise Pascal − CS 20085
63178 Aubière − France

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Post doctorat sur projet ANR FORGECO

Vidéo de soutenance et manuscrit de thèse: soutenance et manuscrit de thèse

Liste de Publications et résumés

Articles de revues scientifiques

B. Bonte, J.-D. Mathias et R. Duboz : Moment approximation of infection dynamics in a population of moving hosts. PLoS ONE, 7(12), 2012 Summary :The modelling of contact processes between hosts is of key importance in epidemiology. Current studies have mainly focused on networks with stationary structures, although we know these structures to be dynamic with continuous appearance and disappearance of links over time. In the case of moving individuals, the contact network cannot be established. Individual-based models (IBMs) can simulate the individual behaviours involved in the contact process. However, with very large populations, they can be hard to simulate and study due to the computational costs. We use the moment approximation (MA) method to approximate a stochastic IBM with an aggregated deterministic model. We illustrate the method with an application in animal epidemiology: the spread of the highly pathogenic virus H5N1 of avian influenza in a poultry flock. The MA method is explained in a didactic way so that it can be reused and extended. We compare the simulation results of three models: 1. an IBM, 2. a MA, and 3. a mean-field (MF). The results show a close agreement between the MA model and the IBM. They highlight the importance for the models to capture the displacement behaviours and the contact processes in the study of disease spread. We also illustrate an original way of using different models of the same system to learn more about the system itself, and about the representation we build of it.

S. Farolfi, J.-P. Muller et B. Bonte : An iterative construction of multi-agent models torepresent water supply and demand dynamics at the catchment level.Environmental Modelling and Software, 25(10):1130–1148, 2010. Summary :Companion Modelling (ComMod) is an iterative approach of modelling in interaction with local stakeholders. KatAWARE is a multi-agent model constructed through a ComMod process with the Water User Association of the Kat River Valley, Eastern Cape, South Africa. By describing the construction of the KatAWARE model, the aim of this paper is to propose a detailed methodology to formalize and to systematize the modelling phases of Companion Modelling. The Kat River catchment will serve as case study for the application of the proposed methodology. This methodology is composed of four steps: (1) the specification of the structure of the system, its dynamics and the indicators one wants to monitor, (2) the description of the initial state of the simulation, (3) the implementation of the model which can take the form of a computer program or of a role-playing game, (4) the reflection step to criticize the model and to propose further improvements. For the first two steps, we propose to use a representation based on the Unified Modelling Language.

Raphaël Duboz, Bruno Bonte et Gauthier Quesnel : Vers une spécification desmodèles de simulation de systèmes complexes. Modélisation informatique et mathématique des systèmes complexes: avancés méthodologiques. Numéro Spécial de la revue Studia Informatica Universalis, 2011. Résumé:L’adoption d’un protocole partagé pour communiquer les modèles de simulation de systèmes complexes de façon rigoureuse est actuellement nécéssaire. Ce constat est soutenu par la demande croissante en modélisation, non seulement pour comprendre la réalité qui nous entoure, mais également pour faire de l’aide à la décision. La spécification rigoureuse des ces modèles de simulation est essentielle car elle permet leur communication, leur reproduction et donc leur vérification. Dans ce papier, nous proposons de réunir les propositions de deux communautés en modélisation et simulation. La première est la communauté des chercheurs en modélisation individus centrés, ou modélisation à base d’agents. Cette communauté propose un protocole, définit par V. Grimm et al. en 2006, revu en 2010. La seconde est la proposition issue de la communauté des chercheurs en simulation au sens large, qui existe autour de la théorie initiée par B. Zeigler en 1976. Nous faisons le lien entre ces deux communautés à partir d’un article de G. Aumann de 2007 qui introduit la théorie de Zeigler en écologie. Ici, nous proposons et décrivons le cadre général d’une méthode de spécification des modèles de simulation qui permet la reproduction et la vérification, et donc augmente la confiance autour des modèles de simulation de systèmes complexes. Nous proposons l’utilisation d’un formalisme systémique pour la spécification de ce protocole. Néanmoins les aspects techniques et purement formels de la spécification, même s’ils sont fondamentaux, ne sont pas abordés dans ce papier car ils ne sont pas nécessaires à sa compréhension. Ils devront néanmoins être présentés prochainement dans leur totalité pour que le protocole proposé ici soit effectif.

Bruno Bonté, Gauthier Quesnel, Jean-Pierre Müller et Raphaël Duboz, The Experimentation Process Model. Application to multiscale modelling . soumis à Journal of Simulation (JoS) Summary :We present a formal and operational framework to specify and automatize experimentation process. This framework is specified as a generic dynamic system model called the Experimentation process Model (EPM) using the Discrete EVent System Specication (DEVS) formalism. Consequently it benets from interesting DEVS properties regarding coupling, such as communicability, modularity and reusability. It enables coupling experimentation process with any model of dynamic system specied in DEVS. We illustrate the interest of the EPM with a concrete example of multi-scale modelling in the field of Epidemiology.

Articles parus dans des actes de conférences internationales en informatique avec comité de lecture

B. Bonté, R. Duboz et J.P. Muller. Modeling the Minsky triad: A Framework to Perform Reflexive M&S Studies. In the proceedings of the Winter Simulation Conference ( ACM/IEEE), C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A. M. Uhrmacher, eds. Berlin, Germany December 9-12 2012 Summary:In this paper, we propose a general framework to evaluate models of systems that are ill defined, incompletely known, and furthermore, which cannot be experimented in real conditions, such as the economical systems at the country scale, epidemics (for obvious ethical reasons) or any natural disasters, for instance where human lives are the main issue. Our framework relies on the generic Marvin Minsky’s definition of a model and its specification in the frame of the Theory of Modeling and Simulation, initiated by B.P. Zeigler. Such a dynamic system vision of the Marvin Minsky model definition enables to address original questions using what we have called the Minsky triad model, i.e. a coupled model composed of the model of the user, the model of a real system, and the model of this later model. We think that the Minsky triad model is very promising as a framework to design decision support systems for crisis management.

Bruno Bonté, Raphaël Duboz, Gauthier Quesnel et Jean-Pierre Müller: Recursive simulation and experimental frame for multiscale simulation. In proceedings of SCSC’09 :Summer Computer Simulation Conference, July 13th-16th 2009. Summary: In this paper, we present a formal and operational framework for multiscale modeling and simulation. We focus on scale transfer viewed as the coupling between two models of the same system, one at the microscopic scale and the other at the macroscopic scale. We consider that some parameters of the macroscopic model are the result of microscopic processes described in the microscopic model. The main idea is to use an “experimenter model” which performs experiments on the microscopic model during the simulation and compute these parameters in line. To formalize the experimental design of the experimenter model, we define an experimental frame of transfer based on Discret Event System Specification. As an example, we present a multi scale model in epidemiology. We specify it using our framework, and we implement and simulate it within the Virtual Laboratory Environment. Finally, we discus some of the scale transfer issues and how we want to use the developed framework to address them.

B. Bonte, E. Penot et J.F. Tourrand : Coupling the farming system modelling tool ’olympe’with the multi-agent-system software system ’cormas’ to understand the use of resources in complexagricultural systems. In proceedings of ECMS'05 - 19th European Conference on Modelling and Simulation, Pages 544–551, 2005. Summary: This paper describes how the farming system modelling software ‘Olympe’ (developed in collaboration by INRA/CIRAD/IAMM) can be coupled with the agent-based simulation platform ‘Cormas’ to better characterize and analyse farming systems identified as major centres of decision in agriculture. Cormas (developed by CIRAD) enables representation of complex situations and takes into account interactions between different stakeholders. First we describe the two models and the potential benefits of combining the tools, then we describe how we developed a new platform based on the two software systems, and finally we illustrate how the new platform can be used with a simple example developed for educational purposes. The advantages and limits of this type of approach are discussed along with possible further developments.

Atricles parus dans des actes de conférences en français

Bruno Bonte, Francois Bousquet, Jean-Pierre Muller, Frederick Pellegrin et Olivier Bonato : Modelling framework for emerging risks simulation in the field ofphytosanitary crisis linked to diseases and bio-invasions. In Proceedings of Biodiversite et Changements climatiques et 8eme Conference Internationale sur les Ravageurs en Agriculture, Montpellier (France) AFPP, p. 594-603, Octobre 21-23 2008. Résumé:Dans le cadre d’une approche systémique des crises phytosanitaires (cas emblématique du risque TYLCV-Bemisia), une plateforme prototype de formalisation et de simulation a été dédiée à l’intégration des composantes épidémiologiques, biotechniques, socio- économiques, réglementaires et organisationnelles. La plateforme est en cours de réalisation suivant une méthodologie qui permet de la concevoir en partenariat avec des chercheurs de champs disciplinaires divers et différents acteurs afin qu’elle puisse répondre à la fois aux questions relatives à l’émergence du risque et à sa gestion en termes de gouvernance territoriale.

Communication dans des conférence internationales

T. Vergne, V. Grosbois, S. San, S. Sothyra, F. Goutard, B. Bonté, A. Bouchot, F. Roger, B. Dufour : How to design a second source for an effective capture-recapture analysis? Conference of the Association of Institutes for TropicalVeterinary Medicine. Présentation orale à la conférence (AITVM), Bangkok, Thailand, 22-26 August 2010 Summary: Use of an Individual-Based Model to test a statistical method of capture-recapture for epidemics surveillance.

B. Bonté, R. Duboz. A modular simulation tool to help designing epidemics surveillance: Work in Progress. Poster à la conférence ICAHS, Lyon 17-20 mai 2011 Summary:There is nowadays a need of new surveillance systems, lighter, cheaper and quantitatively evaluated. Hence, new statistical tools are being developed and new surveillance systems are being designed. Then raise the issues of evaluating these new surveillance systems and build a clear view of their implementation, shared by researchers, actors and decision makers. In order to address these issues, we are building a modular and multi-formalisms simulation tool that allows simulating both the disease spread, and its surveillance. This simulation tools is a framework that can be used in two ways: Firstly to visualize at the same time epidemic spread and surveillance on didactic interfaces; and secondly to perform intensive simulation plans in order to test surveillance protocols in different scenarios. This is a work in progress, the basic structure has been implemented using Discrete Event System specification and the Virtual Laboratory Environment software system. Future work will be to implement a case study and to introduce the disease control component, which is essential to surveillance evaluation.

Raphaël Duboz, Stéphanie Desvaux, Vladimir Grosbois, Bruno Bonté. Simulation of avian flu propagation in the poultry industry network of the north Vietnam. Poster à la conférence Epidemics2, Athens, Greece, 2-4 December 2009.

Chapitre d'ouvrage

Bruno Bonté, Eric Penot, Christophe. Le Page et Jean-François Tourrand : modélisation des exploitations agricoles avec Olympe (Seconde édition), chapitre : Liaison d’un outil de modélisation d’exploitations agricoles (Olympe) avec une plate forme de modélisation multi-agents (Cormas). Quae, 2011.

Soutenance & Manuscrit de Thèse

Vidéo de soutenance de thèse: { { : people: bruno.bonte: 2011-12-16pm_these-brunobonte.webm|320×240} }

Manuscrit de thèse : these_bonte.pdf