Displaying 10 of 51 results agent-based models clear search
The goal of my research program is to improve our understanding about highly integrated natural and human processes. Within the context of Land-System Science, I seek to understand how natural and human systems interact through feedback mechanisms and affect land management choices among humans and ecosystem (e.g., carbon storage) and biophysical processes (e.g., erosion) in natural systems. One component of this program involves finding novel methods for data collection (e.g., unmanned aerial vehicles) that can be used to calibrate and validate models of natural systems at the resolution of decision makers. Another component of this program involves the design and construction of agent-based models to formalize our understanding of human decisions and their interaction with their environment in computer code. The most exciting, and remaining part, is coupling these two components together so that we may not only quantify the impact of representing their coupling, but more importantly to assess the impacts of changing climate, technology, and policy on human well-being, patterns of land use and land management, and ecological and biophysical aspects of our environment.
To achieve this overarching goal, my students and I conduct fieldwork that involves the use of state-of-the-art unmanned aerial vehicles (UAVs) in combination with ground-based light detection and ranging (LiDAR) equipment, RTK global positioning system (GPS) receivers, weather and soil sensors, and a host of different types of manual measurements. We bring these data together to make methodological advancements and benchmark novel equipment to justify its use in the calibration and validation of models of natural and human processes. By conducting fieldwork at high spatial resolutions (e.g., parcel level) we are able to couple our representation of natural system processes at the scale at which human actors make decisions and improve our understanding about how they react to changes and affect our environment.
land use; land management; agricultural systems; ecosystem function; carbon; remote sensing; field measurements; unmanned aerial vehicle; human decision-making; erosion, hydrological, and agent-based modelling
Applying agent-based models to archaeological data, using modern ethnoarchaeological data as an analog for behavior.
Volker Grimm currently works at the Department of Ecological Modelling, Helmholtz-Zentrum für Umweltforschung. Volker does research in ecology and biodiversity research.
How to model it: Ecological models, in particular simulation models, often seem to be formulated ad hoc and only poorly analysed. I am therefore interested in strategies and methods for making ecological modelling more coherent and efficient. The ultimate aim is to develop preditive models that provide mechanstic understanding of ecological systems and that are transparent and structurally realistic enough to support environmental decision making.
Pattern-oriented modelling: This is a general strategy of using multiple patterns observed in real systems as multiple criteria for chosing model structure, selecting among alternative submodels, and inversely determining entire sets of unknown model parameters.
Individual-based and agent-based modelling: For many, if not most, ecological questions individual-level aspects can be decisive for explaining system-level behavior. IBM/ABMs allow to represent individual heterogeneity, local interactions, and/or adaptive behaviour
Ecological theory and concepts: I am particularly interested in exploring stability properties like resilience and persistence.
Modelling for ecological applications: Pattern-oriented modelling allows to develop structurally realistic models, which can be used to support decision making and the management of biodiversity and natural resources. Currently, I am involved in the EU project CREAM, where a suite of population models is developed for pesticide risk assessment.
Standards for model communication and formulation: In 2006, we published a general protocol for describing individual- and agent-based models, called the ODD protocol (Overview, Design concepts, details). ODD turned out to be more useful (and needed) than we expected.
Smarzhevskiy Ivan, born 1961, graduated from the Faculty of Mechanics and Mathematics of Moscow State University in 1983. Ph.D. in Economic Sciences since 2000.
Research interests: individual and collective behavior in the organization, decision making, sociology of small groups.
decision making, sociology of small groups, agent based models
Agent Based Models used in policy analysis
My dissertation research at the Johnson-Shoyama Graduate School of Public Policy focuses on food safety and consumer choices, using agent-based models as a novel method for investigating this policy space.
Andrew Bell (Ph.D. 2010, Michigan) was a Research Fellow in the Environment and Production Technology Division at the International Food Policy Research Institute (IFPRI) in Washington, DC. His current research portfolio focuses on the use of field instruments – such as discrete choice experiments, framed field experiments, randomized control trials – to inform behavior in agent-based models of coupled human-natural systems. Prior to this post, Andrew was a post-doctoral research fellow at The Earth Institute at Columbia University, where he focused on developing applications for paleo-climate histories.
I have been researching in synchronization between agent-based-models (ABM) and multi robot systems used in logistic and manufacturing. I use Netlogo as ABM.
I develop and agile methodology to use the same ABM as supervisory control and data aquisition (SCADA). The framework works fine and I test it in two SCADAs, which you can see in my youtube channel (http://www.youtube.com/channel/UCJIb_UL-ak98F5OZxOHL0FQ).
Agent-based models of human behaviour, from cognitive modelling through to cognitively-rich social simulation.
Using Bayesian statistics for improving Agent based models and visa versa.
Displaying 10 of 51 results agent-based models clear search