PECS #2: Agent-based modeling with Jacopo Baggio

Agent-based models have been increasingly applied in social and ecological systems to uncover emergent properties of systems via individual agents’ behavior and interactions. Agent-based modeling allows for a system to be represented from the “bottom-up”. Modeling individual agents and their interactions allow us to assess the emergence of general patterns often not inferable by observing just the individual interactions. This, in turn, can help to inform our understanding of complex systems in cases where experimentation is impossible and/or unethical.

In this webinar I introduce agent-based models, what they are, the modeling building process and potential issues when devising, implementing and analyzing agent based models. I will then present two agent based models representing how individual “managers” may or may not collaborate and share strategies in order to 1) manage ecological disturbances such as biological invasions, fires etc., and 2) manage biodiversity by facilitating or hindering species movement. Both are models, hence simplified versions of reality, that mimic multiple political jurisdictions making decisions affecting either the propagation of ecological disturbances or species migration across a landscape.

Jacopo is an Assistant Professor at the University of Central Florida, School of Politics, Security, and International Affairs,  and member of the National Center for Integrated Coastal Research and of the Sustainable Coastal Systems Cluster. He holds a BA in Economic and Social Sciences from the University of Milan Bicocca, a Master in Development Economics and a PhD in International Development from the University of East Anglia. He worked as an Assistant Professor in the department of Environment and Society, at Utah State University and as a postdoctoral research associate at the Center for Behavior, Institutions and the Environment (CBIE), Arizona State University. His current research focuses on understanding and managing Social-Ecological systems integrating agent-based modeling, networks and behavioral experiments.