This model was developed as part of my MSc thesis in the Engineering and Policy Analysis program at Delft University of Technology. The model represents a refugee camp with household agents who are connected by a social network. Grounded in innovation diffusion theory and a case study, the agents go through five decision stages, facing different adoption barriers, and ultimately decide whether or not to adopt and keep using clean cooking fuels. Interactions between agents include flows of information and social conformity effects. The aim is to analyse the impact of different interventions on the adoption of clean cooking fuels in refugee camps under a wide range of scenarios.
The model is based on the agent-based modelling approach and implemented using Mesa in Python. The exploratory analysis of the model outcomes uses the EMA workbench (https://emaworkbench.readthedocs.io/en/latest/).
- Model.py: Contains the model class and the agent class.
- Server.py: Defines classes for visualizing the model in the browser using Mesa's modular server.
- EMA.ipynb: Contains the experimentation and exploratory analysis of the model using the EMA workbench.
A description of the model can be found in the thesis under the same name available in the TU Delft repository (https://repository.tudelft.nl/).