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Table of contents
0.1 Acknowledgement
0.2 Abstract
1 Introduction
1.1 Context
1.2 Motivations and Research questions
2 STATE OF THE ART
2.1 Why coupling models ?
2.1.1 Model
2.1.2 Models Coupling
2.1.3 Advantages of coupling
2.2 Different kinds of coupling
2.2.1 Weak coupling
2.2.2 Strong coupling
2.3 Challenges of model coupling
2.3.1 Reusability
2.3.2 Scalability
2.3.3 Expressivity
2.3.4 Flexibility
2.4 Existing solutions in modeling/simulation
2.5 Conclusions
3 CO-MODEL: AN INFRASTRUCTURE FOR SUPPORTING THE DYNAMICAL COUPLING OF HETEROGENEOUS MODELS
3.1 Introduction
3.2 Basic concepts
3.2.1 Co-model
3.2.2 Micro-model
3.3 Integration in the GAMA platform
3.3.1 Why GAMA?
3.3.2 Implementation
3.3.3 Portability
3.4 Example of use (syntaxes)
3.4.1 Importation
3.4.2 Instantiation
3.4.3 Execution
3.5 End of chapter
4 Demonstration and usage
4.1 Objective
4.2 Toy model description
4.3 Toy model implementation
4.3.1 The animal-resource model
4.3.2 The prey-predator model
4.4 Co-modeling
4.4.1 Step by step co-modeling the prey-predator co-model
4.5 Discussion
4.5.1 Reusability
4.5.2 Expressivity
4.5.3 Scalability
4.5.4 Flexibility
5 Dynamic choice of the best representation of a phenomenon
5.1 Objective
5.2 Modeling context
5.3 Definition of micro-models
5.4 Transformation of the Switch model into a co-model
5.4.1 Dynamics of co-model
5.5 Conclusion
6 Incremental design of a complex integrated model
6.1 Objective
6.2 Modeling context
6.3 Definition of micro-models
6.3.1 Farmers behaviors model (M_F)
6.3.2 Salinity intrusion model (M_S)
6.3.3 Parcels model (M_P)
6.3.4 Economical model (M_E)
6.3.5 Farmers relationships model (M_N)
6.3.6 Summary on the micro-models
6.4 Impact of environmental factors on farmers’ decisions
6.4.1 Implementation
6.5 Coupling of Farmer and Socio-Economy factors
6.5.1 Implementation
6.6 Coupling environmental, social and economic models
6.6.1 Implementation
6.6.2 Experimentation
6.7 Conclusion
7 Conclusion
