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Tenured researcher @ government think-tank (IPEA) and CNPq (productivity grant - since 2014), complex modeler interested, data fan, transitional Python user, PhD. Background in urban analysis, economics, geography. From twitter.com/furtadobb
Agent-based modeling, urban policy, urban economics. Metropolis and municipalities analyses.
Annie Waldherr is a postdoctoral researcher at the Free University of Berlin, Institute for Media and Communication Studies. In 2012, she received her PhD for her dissertation on the dynamics of media attention. Her research interests include modeling public spheres, political online communication as well as science and technology discourses.
My main research field is health economic modeling with the main focus on sexually transmitted diseases. We are trying to build a agent-based model using the FLAME-framework (www.flame.ac.uk).
Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.
Water resource economics, natural resource economics, environmental economics, ecological economic modeling, ecological economics, environmental policy, development economics.
Andrew J. Collins, Ph.D., is an associate professor at Old Dominion University in the Department of Engineering Management and Systems Engineering. He has a Ph.D. in Operations Research from the University of Southampton, and his undergraduate degree in Mathematics was from the University of Oxford. He has published over 80 peer-review articles. He has been the Principal Investigator on projects funded to the amount of approximately $5 million. Dr. Collins has developed several research simulations including an award-winning investigation into the foreclosure contagion that incorporated social networks.
Agent-based Modeling
Agent-based simulation
Cooperative Game Theory
Behavior modeling
I am an environmental archaeologist, specializing in charcoal analysis, computational and analytical proxy modeling, and quantitative methods to understand the dynamic relationship between fire, humans, and long-term environmental change. I work primarily in the Western United States and the Western Mediterranean. I am passionate about our public lands and ensuring that everyone has access and opportunity to experience them.
Envrionmental Archaeology, Fire Ecology, GIS, Agent-based modeling, Geoarchaeology
I study small- and large-scale sustainable resource management using a variety of techniques including mathematical modeling, agent-based simulation, and Statistical Inference
Human-Environment relations
socio-ecological systems
Transitions
Simulation modeling
Dr. Aaron Bramson is principal investigator of the AI Strategy Center of GA technologies in Tokyo, Japan, as well as an Affiliate Researcher in the Department of General Economics of Ghent University in Belgium. His research specialty is complexity science, especially methodologies for modeling complex systems. Research topics span across disciplines: measures of polarization and diversity, belief measure interoperability, integrating geospatial and network analyses for measuring walkability and neighborhood identification, and myriad applications in artificial intelligence and data visualization. He received his Ph.D. from the University of Michigan in a joint program with the departments of Political Science and Philosophy as well as an M.S. in Mathematics from Northeastern University.
Complex systems, agent-based modeling, social simulation, computational models, network models, network theory, methodology, philosophy of science, ontology, epistemology, ethics, artificial intelligence, big data analysis, geospatial data analysis,
Displaying 10 of 186 results modeling clear search