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Modeling land use change from smallholder agricultural intensification
Agricultural expansion in the rural tropics brings much needed economic and social development in developing countries. On the other hand, agricultural development can result in the clearing of biologically-diverse and carbon-rich forests. To achieve both development and conservation objectives, many government policies and initiatives support agricultural intensification, especially in smallholdings, as a way to increase crop production without expanding farmlands. However, little is understood regarding how different smallholders might respond to such investments for yield intensification. It is also unclear what factors might influence a smallholder’s land-use decision making process. In this proposed research, I will use a bottom-up approach to evaluate whether investments in yield intensification for smallholder farmers would really translate to sustainable land use in Indonesia. I will do so by combining socioeconomic and GIS data in an agent-based model (Land-Use Dynamic Simulator multi-agent simulation model). The outputs of my research will provide decision makers with new and contextualized information to assist them in designing agricultural policies to suit varying socioeconomic, geographic and environmental contexts.
For my Ph.D. thesis, I developed a system to play poker.
I’m interested to see whether a similar approach can be applied to agent based models.
Cheick Amed Diloma Gabriel Traore is a researcher specializing in modeling multi-agent systems. He earned his PhD from Cheikh Anta Diop University (UCAD) in Senegal. His doctoral research focused on the formalization and simulation of Sahelian transhumance as a complex adaptive system. Utilizing mathematical and computational techniques, he developed agent-based models to analyze the spatiotemporal dynamics of transhumant herds, taking into account factors such as herd behavior, environmental conditions, and socio-economic pressures.
To design the models for his dissertation, Cheick conducted extensive fieldwork in Senegal. He collaborated with interdisciplinary teams to collect data on transhumant practices within the Sahelian ecosystem. With this data, he created a multi-objective optimization framework to model the movement decisions of transhumants and their herds. Additionally, he developed a real-time monitoring system for transhumant herds based on discrete mathematics. His doctoral research was funded by the CaSSECS project (Carbon Sequestration and Sustainable Ecosystem Services in the Sahel).
Before pursuing his PhD,Cheick obtained both a master’s and a bachelor’s degree in mathematics from Nazi Boni University in Burkina Faso. During his studies, he developed a rectangular grid for image processing and applied the Hough transform to detect discrete lines. His master’s and bachelor’s degrees were funded by the Burkinabe government.
Currently,Cheick is an Assistant Professor at the Institute of Computer Engineering and Telecommunications at the Polytechnic School of Ouagadougou. In addition to his role in student training, he is working on integrating viability theory with agent-based modeling to address sustainable development challenges in rapidly changing and complex socio-economic systems. His research has been published in several renowned conferences and scientific journals, and he continues to actively contribute to the fields of complex systems modeling and image processing.
Agent Based Modeling, Machine Learnig, Deep Learning, Numerical Analysis
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IRPact - An integrated agent based modeling approach in innovation diffusion
Goal: The goal of IRPact is to develop a flexible and generic innovation-diffusion ABM (agent-based modelling) framework, based on requirements derived from a literature analysis. The aim of IRPact is to allow for modeling a large number of application contexts and questions of interest.
It provides a formal model (framework) as well as a software implementation in order to assist modelers with a basic infrastructure for their own research.
Conceptually it is thought to be part of the IRPsim (https://irpsim.uni-leipzig.de), with the vision to bring together rational approaches and cognitive modeling in an integrated approach within the context of sustainable energy markets.
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