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Agent Based Modeling (ABM), Agent Based Social System (ABSS), Multi-Agent Systems (MAS), Bayesian learning, Social networks Analysis (SNA), Socio ecological Dynamics.
PhD student at University of Toronto: memes, social networks, contagion, agent based modeling, synthetic populations
As publically funded science has become increasingly complex, the policy and management literature has begun to focus more attention on how science is structured and organized. My research interests reside at the nexus of science and technology policy, organizational theory, and complexity theory—I am interested in how the management and organization of S&T research influences the implementation of policies and the emergence of organizational strategies and innovation. Although my research involves the use of multiple qualitative and quantitative methods, I rely heavily on agent based modeling and system dynamics approaches in addressing my research questions.
I discovered at the same time Agent-Based Modeling method and Companion Modelling approach during my master degrees (engeenering and artificial intelligence and decision) internship at CIRAD in 2005 and 2006 where I had the opportunity to participate as a modeller to a ComMod process (Farolfi et al., 2010).
Then, during my PhD in computer Science applied to Modeling and Simulation, I learned the Theory of Modeling and Simulation and the Discrete EVent System specification formalism and proposed a conceptual, formal and operational framework to evaluate simulation models based on the way models are used instead of their ability to reproduce the target system behavior (Bonté et al., 2012). Applied to the surveillance of Epidemics, this work was rather theoritical but very educative and structuring to formulate my further models and research questions about modeling and simulation.
From 2011 to 2013, I worked on viability theory applied to forest management at the Compex System Lab of Irstea (now Inrae) and learned about the interest of agregated models for analytical results (Bonté et al, 2012; Mathias et al, 2015).
Since 2013, I’m working for Inrae at the joint The Joint Research Unit “Water Management, Actors, Territories” (UMR G-EAU) where I’m involved in highly engaging interdisciplinary researches such as:
- The Multi-plateforme International Summer School about Agent Based Modelling and Simulation (MISSABMS)
- The development of the CORMAS (COmmon Pool Resources Multi-Agents Systems) agent-based modeling and simulation Platform (Bommel et al., 2019)
- Impacts of the adaptation to global changes using computerised serious games (Bonté et al., 2019; Bonté et al. , 2021)
- The use of experimentation to study social behaviors (Bonté et al. 2019b)
- The impact of information systems in SES trajectories (Paget et al., 2019a)
- Adaptation and transformations of traditional water management and infrastructures systems (Idda et al., 2017)
- Situational multi-agent approaches for collective irrigation (Richard et al., 2019)
- Combining psyhcological and economical experiments to study relations bewteen common pool resources situations, economical behaviours and psychological attitudes.
My research is about modelling and simulation of complex systems. My work is to use, and participate to the development of, integrative tools at the formal level (based on the Discrete EVent System Specification (DEVS) formalism), at the conceptual level (based on integrative paradigms of different forms such as Multi-Agents Systems paradigm (MAS), SES framework or viability theory), and at the level of the use of modelling and simulation for collective decision making (based on the Companion Modelling approach (ComMod)). Since 2013 and my integration in the G-EAU mixt research units, my object of studies were focused on multi-scale social and ecological systems, applied to water resource management and adaptation of territories to global change and I added experimentation to my research interest, developping methods combining agent-based model and human subjects actions.
As a data scientist, I employ a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I also apply Science and Technology Studies lenses to my modeling processes in order to see potential ways to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling: teaching mapping and modeling skills, collaboratively building data representations and models, and analyzing and synthesizing community-held data as appropriate. At the same time, I look for ways to create space for qualitative and other forms of knowledge to reside alongside quantitative analysis, using mixed and integrative methods.
Recent projects include: 1) Studying Californian forest dynamics using Bayesian statistical models and object-based image analysis (datasets included forest inventories and historical aerial photographs); 2) Indigenous mapping and community-based modeling of agro-pastoral systems in rural Zimbabwe (methods included GPS/GIS, agent-based modeling and social network analysis); 3) Supporting Tribal science and environmental management on the Klamath River in California using historical aerial image analysis of land use/land cover change and social networks analysis of water quality management processes; 4) Bayesian statistical modeling of community-collected data on human uses of Marine Protected Areas in California.
Applications of agent-based modeling and complexity theory to real-world problems. I am particular interested in stigmergic polyagents, their relation to the path integral formalization of quantum physics, and their application to combinatorially explosive problems, but also work extensively in modeling social systems.
Agent Based Modeling And Simulation
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.
modeling infection system using agent-based modeling
Displaying 10 of 93 results Agent-based modeling clear search