I hold an MA degree in Economics from Boston University (USA) and recently receiving a PhD in Systems Science from Portland State University (USA). With the goal of specializing in the analysis of social-ecological systems, my pursuit of a degree in Systems Science allowed me to integrate training in systems theory, methods, and tools with select study in the behavioral (psychology), social (economics, sociology) and environmental (forest ecology, sustainability) sciences.
My dissertation work involved developing and applying a comprehensive cross-disciplinary toolkit, called SOSIEL (Self-Organizing Social and Inductive Evolutionary Learning), for modeling boundedly-rational (real-world) decision-making in social contexts. Through its six components, the SOSIEL toolkit provides guidance in designing, building, operationalizing, analyzing, and testing a new generation of cognitive multi-agent knowledge-based models in which each agent is empowered with its own cognitive architecture consisting of theoretically-grounded cognitive processes and agent-specific empirically-grounded knowledge. These models are able to simulate the cross-generational progression of SOSIEL agents, which interact among themselves and/or with coupled natural and/or technical systems, learn from their and each other’s experience, create new practices, and make decisions about taking and then take (potentially collective) actions.
Cognitive Social Science, Social-Ecological Systems, Multi-Agent Modeling, Complex Adaptive Systems
The model simulates seven agents engaging in collective action and inter-network social learning. The objective of the model is to demonstrate how mental models of agents can co-evolve through a complex relationship among factors influencing decision-making, such as access to knowledge and personal- and group-level constraints.