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
This paper investigates how collective action is affected when the interaction is driven by the underlying hierarchical structure of an organization, e.g., a company. The performance of collection action is measured as the rate of contribution to a public good, e.g., an organization’s objective.
General Question:
Without Central Control is self organization possible?
Specific Case:
Considering the seemingly preplanned, densely aggregated communities of the prehistoric Puebloan Southwest, is it possible that without centralized authority (control), that patches of low-density communities dispersed in a bounded landscape could quickly self-organize and construct preplanned, highly organized, prehistoric villages/towns?
I am a Ph.D. student studying the interactions between external regulations and social norms in natural resource management and international development. In particular, I am looking to use mixed methods research, including ethnographic research, field experiments, and agent-based computational models to explore the sustainability of market-based interventions and their possible perverse outcomes.
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.
I am a computer scientist by training and full stack software engineer / systems administrator and have been building cyberinfrastructure for computational social science at ASU since 2006; these projects include the Digital Archaeological Record, the Virtual Commons, the Social Ecological Systems Library, and CoMSES Net, where I serve as a co-director.
I’m also a Software / Data Carpentries maintainer and instructor and a member of the Force 11 Software Citation Implementation Working Group.
My research interests include collective action, social ecological systems, large-scale software systems engineering, model componentization and coupling, and finding effective ways to promote and facilitate good software engineering practices for reusable & reproducible scientific computation.