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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).
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Klaus G. Troitzsch was a full professor of computer applications in the social sciences at the University of Koblenz-Landau since 1986 until he officially retired in 2012 (but continues his academic activities). He took his first degree as a political scientist. After eight years in active politics in Hamburg and after having taken his PhD, he returned to academia, first as a senior researcher in an election research project at the University of Koblenz-Landau, from 1986 as full professor of computer applications in the social sciences. His main interests in teaching and research are social science methodology and, especially, modelling and simulation in the social sciences.
Among his early research projects there is the MIMOSE project which developed a declarative functional simulation language and tool for micro and multilevel simulation between 1986 and 1992. Several EU funded projects were devoted to social simulation and policy modelling, the most recent from 2012 to 2015 combining data/text mining and agent-based simulation to analyse the global dynamics of extortion racket systems.
He authored, co-authored, and co-edited several books and many articles in social simulation, and he organised or co-organised a number of national and international conferences in this field. Over nearly three decades he advised and/or supervised more than 55 PhD theses, most of them in the field of social simulation. He offered annual summer and spring courses in social simulation between 1997 and 2009; more recent courses of this kind are now being organised by the European Social Simulation Assiciation and held at different places all over Europe (mostly with his contributions).
Computational social science, structuralist theory reconstruction
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I am a computational archaeologist interested in how individuals and groups respond to both large scale processes such as climate change and local processes such as violence and wealth inequality. I am currently a PhD Candidate in the Department of Anthropology at Washington State University.
My dissertation research focuses on experimenting with paleoecological data (e.g., pollen) to assess whether or not different approaches are feasible for paleoclimatic field reconstructions. In addition, I will also use pollen data to generate vegetation (biome) reconstructions. By using tree-ring and pollen data, we can gain a better understanding of the paleoclimate and the spatial distribution of vegetation communities and how those changed over time. These data can be used to better understand changes in demography and how people responded to environmental change.
In Summer 2019, I attended the Santa Fe Institute’s Complex Systems Summer School, where I got to work in a highly collaborative and interdisciplinary international scientific community. For one of my projects, I got to merry my love of Sci-fi with complexity and agent-based modeling. Sci-fi agent-based modeling is an anthology and we wanted to build a community of collaborators for exploring sci-fi worlds. We also have an Instagram page (@Scifiabm).
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.
I am a multidisciplinary researcher and artist. I have worked as a global health researcher since 2015, studying malaria prevention and control, medical entomology, and epidemiology. I am a Ph.D candidate at the University of Montreal’s School of Public Health. For my doctoral research, I deploy complex systems methodologies and frameworks from Science, Technology and Society to examine the processes of health systems strengthening in vulnerable populations
My work explores the political economy of disease prevention and control (global health), the political ecology of the intersections between human, animal and ecosystem health (planetary health), and how complimentary expertises can be mobilized to effectively improve the well-being of underserved and remote communities sustainably through participatory processes (transdisciplinary, community-based research).
Ken Buetow is a human genetics and genomics researcher who leverages computational tools to understand complex traits such as cancer, liver disease, and obesity. He currently serves as director of Computational Sciences and Informatics program for Complex Adaptive Systems at Arizona State University (CAS@ASU), is a professor in the School of Life Sciences in ASU’s College of Liberal Arts and Sciences; is a core faculty in the Center for Evolution and Medicine in the Biodesign Institute at ASU; and is director of bioinformatics and data management for the National Biomarker Development Alliance.
Professor Buetow previously served as the Founding Director of the Center for Biomedical Informatics and Information Technology within the National Institutes of Health’s National Cancer Institute.
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