Course 1: 12 November/Morning
Benoit Gaudou (UMMISCO/IRD and Université Toulouse 1 Capitole, IRIT).
Topic: Modeling and computer simulation for understanding and exploring urban spatial dynamics. Total time: 3h from 9:00 to 12:00.
Representing a real system in all its complexity to measure possible evolutions or to design planning solutions is one of the challenges of current research in computer modeling, especially agent-based modeling. Complementary to classical methods, this approach makes it possible to design models whose dynamics are the result of interactions between computer representations of the entities of the modeled system (actors, institutions, environment, facilities, etc.). These models then serve as a support for a "virtual" experimental approach - using simulations - where the resulting dynamics can be studied with all the necessary details, and where interaction with the user is encouraged.
The objective of the course is to make students aware of computer modeling methodologies of different urban dynamics (mobility, segregation, evacuation, growth ...) based on the presentation of several case studies. It will rely particularly on the construction and experimentation of models in the GAMA modeling platform (http://gama-platform.org)
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Course 2: 12 November/Afternoon
Nguyen Ngoc Doanh (WARM, UMMISCO, IRD/France and Thuyloi University)
Topic: Coupling agent-based and mathematical modeling approaches to explore complex systems. Total time: 3h from 9:00 to 12:00.
We will give lectures on coupling the agent-based and mathematical modeling approaches in the study of some interesting ecosystems such as competition and disease systems. Each modeling approach has its own strengths and weakness and can be seen as an aspect/view when it comes to model complex systems. On one hand, agent-based models are computer based models where environment, interaction among agents as well as between them and environment are explicitly represented in a computer program. It is kind of microscopic view of systems. Inversely, mathematical models are compartment models based on some, normally physic and biology/ecology laws. It is a macroscopic way to look at the evolution of systems. We will present a way to use these two different but complementary approaches to explore complex systems.
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Course 3: 13 November/Morning
Tri Nguyen-Huu, UMMISCO, IRD, France
Population dynamics. Total time: 3h from 9:00 to 12:00.
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We will introduce mathematical tools for dynamical systems, in particular for systems of ordinary differential equations. We will present several classical models in theoretical models for population dynamics. We will focus on interaction models, like prey-predator or competition models. We will then describe how such model can be extended to real case studies, such as the description of ecosystems in National Parks in Kenya.
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Course 4: 13 November/Afternoon
Pierre Auger, UMMISCO, IRD, France
Fishery modeling. Total time: 3h from 9:00 to 12:00.
The framework of dynamical systems is intensely used in the context of fishery modeling. We will provide an introduction to the modeling of the exploitation of renewable resources and the impact on the economy and the biodiversity. Several case studies will be presented related to marine protected areas and fish economy in the Atlantic coast of Morocco and Senegal.