Agent-based modeling is a flexible and intuitive approach that is close to both data and theories, which gives it a special position in the majority of scientific communities. Agent models are as much tools of understanding, exploration and adaptation as they are media for interdisciplinary exchange. It is in this kind of framework that this book is situated, beginning with agent-based modeling of spatialized phenomena with a methodological and practical orientation.

Through a governing example, taking inspiration from a real problem in epidemiology, this book proposes, with pedagogy and economy, a guide to good practices of agent modeling. The reader will thus be able to understand and put the modeling into practice and acquire a certain amount of autonomy.

Featuring the following well-known techniques and tools: Modeling, such as UML, Simulation, such as the NetLogo platform, Exploration methods, Adaptation using participative simulation

About the Authors

Arnaud Banos is CNRS research director and head of the UMR G�ographie-cit�s (CNRS –Panth�on-Sorbonne University – Paris Diderot University, France). As a geographer, he favors an interdisciplinary approach to complex spatial systems.

Christophe Lang is Associate Professor of Computer Science at the University of Franche-Comt� in France, within the FEMTO-ST, UMR 6174 laboratory. He conducts research in the field of distributed systems and more specifically in the field of multi-agent systems.

Nicolas Marilleau is a research engineer at UMI 209 UMMSICO of the Institut de Recherche pour le D�veloppement in France. He conducts research in the field of modeling-simulation agents for complex systems, which he applies to real problems together with researchers in other disciplines.

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