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IRPact - An integrated agent based modeling approach in innovation diffusion
Goal: The goal of IRPact is to develop a flexible and generic innovation-diffusion ABM (agent-based modelling) framework, based on requirements derived from a literature analysis. The aim of IRPact is to allow for modeling a large number of application contexts and questions of interest.
It provides a formal model (framework) as well as a software implementation in order to assist modelers with a basic infrastructure for their own research.
Conceptually it is thought to be part of the IRPsim (https://irpsim.uni-leipzig.de), with the vision to bring together rational approaches and cognitive modeling in an integrated approach within the context of sustainable energy markets.
modeling infection system using agent-based modeling
Topics:
Behavioural aspects of environmental problems: Use of evolutionary approaches to investigate how people react to environmental policy.
Resource scarcity
Climate-economic Models: Understand how economic agents think and decide about climate change and climate protection
Sustainable Development
Methods:
Agent-Based-Modeling
Genetic algorithms
Evolutionary economics
Behavioural economics
Ecological economics
Complexity Theory
Dr. Kimberly G. Rogers studies the coupled human-natural processes shaping coastal environments. She obtained a B.Sc. in Geological Sciences from the University of Texas at Austin and began her graduate studies on Long Island at Stony Brook University’s School of Marine and Atmospheric Sciences. Rogers completed her Ph.D. at Vanderbilt University, where she specialized in nearshore and coastal sediment transport. She was a postdoctoral scholar and research associate at the Institute for Arctic and Alpine Research at the University of Colorado Boulder. In 2014, her foundation in the physical sciences was augmented by training in Environmental Anthropology at Indiana University Bloomington through an NSF Science, Engineering, and Education for Sustainability (SEES) Fellowship.
Rogers’s research is broadly interdisciplinary and examines evolving sediment dynamics at the land-sea boundary, principally within the rapidly developing river deltas of South Asia. As deltas are some of the most densely populated coastal regions on earth, she incorporates social science methods to examine how institutions — particularly those governing land use and built infrastructure — influence the flow of water and sediment in coastal areas. She integrates quantitative and qualitative approaches in her work, such as direct measurement and geochemical fingerprinting of sediment transport phenomena, agent-based modeling, institutional and geospatial analyses, and ethnographic survey techniques. Risk holder collaboration is an integral part of her research philosophy and she is committed to co-production and capacity building in her projects. Her work has gained recognition from policy influencers such as the World Bank, USAID, and the US Embassy Bangladesh and has been featured in popular media outlets such as Slate and Environmental Health Perspectives.
André Calero Valdez does research on Computational Communication Science investigating the influence of network structure and algorithms on communication flow using agent-based modeling.
This is Saeed Abdolhosseini. I am very interested in the area of agent based modeling and it is about 3 years that I am working on Agent-Based Modeling. I have a good experience of working with Netlogo &Repast simphony & Anylogic. I have developed a few ABM application.
Specialties: Agent-based models of social systems
Agent Based Modeling
Agent-based Modeling, Maching Learning, Algorithmic Marketing, Diffusion of Innovations, Online Communities
My broad research interests are in human-environmental interactions and land-use change. Specifically, I am interested in how people make land-use decisions, how those decisions modify the functioning of natural systems, and how those modifications feedback on human well-being, livelihoods, and subsequent land-use decisions. All of my research begins with a complex systems background with the aim of understanding the dynamics of human-environment interactions and their consequences for environmental and economic sustainability. Agent-based modeling is my primary tool of choice to understand human-environment interactions, but I also frequently use other land change modeling approaches (e.g., cellular automata, system dynamics, econometrics), spatial statistics, and GIS. I also have expertise in synthesis methods (e.g., meta-analysis) for bringing together leveraging disparate forms of social and environmental data to understand how specific cases (i.e., local) of land-use change contribute to and/or differ from broader-scale (i.e. regional or global) patterns of human-environment interactions and land change outcomes.
Garry Sotnik is a lecturer at the Stanford Doerr School of Sustainability, teaching human adaptation to climate change, decision-making, and transformative social change.
complexity, agent-based modeling, cognition
BIGSSS-Departs PhD Fellow
Bremen International Graduate School of Social Sciences / Jacobs University (Germany)
PhD project: Residential Segregation and Intergenerational Immigrant Integration: A Schelling-Esser Model
Italian PhD fellow, fond of social complexity and agent-based modeling, applied to residential segregation and integration processes
Research Interests: Agent-based modeling, migrant integration, residential segregation
Displaying 10 of 98 results Agent-based modeling clear search