Former professor at the University of Neuchatel in Switzerland and now senior researcher at CIRAD in France, I am doing research on artificial intelligence since 1984. Having begun with logic programming, I naturally applied logics and its extensions (i.e. modal logics of various sorts) to specify agent behaviour. Since 1987, I moved both to embedded intelligence (using mobile robots) and multi-agent systems applied, in particular, to job-shop scheduling and complex system simulation and design. Since 2001, I exclusively work on modelling and simulation of socio-ecosystems in a multidisciplinary team on renewable resources management (GREEN). I am focusing on modelling complex systems in a multi-disciplinary (economist, agronomist, sociologists, geographers, etc.) and multi-actor (stakeholders, decision makers) setting. It includes:
- representing multiple points of view at various scales and levels on a complex socio-ecosystem, using ontologies and contexts
- representing the dynamics of such systems in a variety of formalisms (differential equations, automata, rule-based systems, cognitive models, etc.)
- mapping these representations into a simulation formalism (an extension of DEVS) for running experiments and prospective analysis.
This research is instantiated within a modelling and simulation platform called MIMOSA (http://mimosa.sourceforge.net). The current applications are the assessment of the sustainability of management transfer to local communities of the renewable ressources and the dynamics of agro-biodidversity through networked exchanges.

I am a Professor in the School of Sustainability and the Director of the Center for Behavior, Institutions and the Environment. I want to understand how people solve collective problems at different levels of scale, especially those problems related to sustainability of our environment. Our society experience unprecedented challenged to sustain common resource for future generations at a scale we have never experienced before. What makes groups cooperate? What is the role of information? How does the ecological context affect the social fabric? How do they deal with a changing environment? How can we use these insight to address global challenges? To do this research I combine behavioral experiments, agent-based modeling and case study analysis.

Area: Complex Biological, Social and Sociotechnical Systems
Specific focus: Origins of intelligent behavior

My research focuses pn the intersection between game theory, social networks, and multi-agent simulations. The objectives of this scientific endeavor are to inform policy makers, generate new technological applications, and bring new insight into human and non-human social behavior. My research focus is on the transformation of cultural conventions, such as signaling and lexical forms, and on many cell models models of stem cell derived clonal colony.

Because the models I analyze are formally defined using game theory and network theory, I am able to approach them with different methods that range from stochastic process analysis to multi-agent simulations.

Ecology - Natural Resources Management (Community-based management)

I worked on natural resources management modelling in STELLA. I developed a technical and scientific model to analyze soil, climate and biological conditions to explain how Bamboo ecosystem works and how people in Cundinamarca, Colombia could focus on a sustainable model for use and manage forestry resources.
Also, I worked on the seventh framework program named: Community-based management of Environmental Challenges in Latin America -COMET-LA-. The project built a learning arena with scientists, civil society and government to identify sustainable models for governance of natural resources in social-ecological systems located in a rural context from Colombia, México and Argentina.

I am interesting in research on Modelling of governance and Community-based management of natural resources.

I work in the field of complex adaptive systems, specializing in multi-agent systems, simulation, machine learning, collective intelligence, self-organization, and self-adaptation. I am interested in contributing to innovative projects and research in these domains.

My experience spans across multiple large-scale international research projects in areas such as green urban logistics, blockchain for nuclear applications, autonomous robotics systems and simulation of biological neural networks.

I am strongly interested in ecological modeling and complex system and truly enjoyed working with a variety of tools to uncover patterns in empirical data and explore their ecological and evolutionary consequences. My primary research is to conduct research in the field of ‘ecological complexity’, including the development of appropriate descriptive measure to quantify the structural, spatial and temporal complexity of ecosystem and the identification of the mechanism that generate this complexity, through modeling and field studies.
Currently investigated is how biological characteristics of invasive species (dispersal strategies and demographic processes) interact with abiotic variables and resource distribution to determine establishment success and spread in a complex heterogeneous environment (Individual based modelling integrated with GIS technologies).

I research the role of local information and stories to increase citizen engagement in urban environments. Through workshops with citizens (children, youngsters and adults), I identify which approaches are suitable to increase engagement through local stories and storytelling. My thesis works towards a toolkit and framework which showcases possible neighbourhoud interventions, presents design guidelines, and discusses trade-offs. The research builds on workshops and projects done in The Hague and Rotterdam.

My research interests include policy informatics and decision making, modeling in policy analysis and management decisions, public health management and policy, and the role of public value in policy development. I am particularly interested in less mainstream approaches to modeling that account for learning, feedback, and other systems dynamics. I include Bayesian inference, agent-based models, and behavioral assumptions in both my research and teaching.
In my dissertation research, I conceptualize state Medicaid programs as complex adaptive systems characterized by diverse actors, behaviors, relationships, and objectives. These systems reproduce themselves through both strategic and emergent mechanisms of program management. I focus on the mechanism by which citizens are sorted into or out of the system: program enrollment. Using Bayesian regression and agent-based models, I explore the role of administrative practices (such as presumptive eligibility and longer continuous eligibility periods) in increasing enrollment of eligible citizens into Medicaid programs.