I am a modeler scientist at CIRAD. As member of the Green Research Unit, I contribute to promote the Companion Modeling approach (http://www.commod.org). Through the development of CORMAS, a Framework for Agent-Based Models (http://cormas.cirad.fr), I have been focusing on the development and the use of multi-agent simulations for renewable resource management issues. I have been based several years in Brazil, at the University of Brasilia and at the PUC-Rio University, until 2014. I developed models related to environmental management, such as breeding adaptation to drought in the Uruguay or as breeding and deforestation in the Amazon. I am currently based in Costa Rica, firstly at the University of Costa Rica working on adaptation of agriculture and livestock to Climate Changes, and now at CATIE, working on coffe rust.
Participatory modeling, including collective design of model and interactive simulation
MY research aims to give artists better 3D references and scene reconstructions which can be directly fed into the creative pipeline. This is motivated by increasing public demand for detailed, complex 3D worlds and the resulting demand this places on world design artists.
This project lookings at developing acquisition and modelling technologies that provide more than just a visual reference: in the context of this project, visual acquisition and reconstruction methods shall be developed that provide richer, three-dimensional references, and that ultimately yield scene reconstructions that can directly be fed into the content creation pipeline. The project will focus on natural environments (as opposed to urban scenes) and may combine multi-spectral imaging, wide-baseline stereo reconstruction and semantic scene analysis to obtain approximate procedural representations of natural scenes.
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Modeling, companion modeling, role playing games, serious games, multi-agent systems, agent-oriented simulation, complex systems, water management, artificial intelligence
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 PhD Candidate in the Biological Anthropology program at the University of Minnesota. My research involves using agent-based models combined with field research to test a broad range of hypotheses in biology. I have created a model, B3GET, which simulates the evolution of virtual organisms to better understand the relationships between growth and development, life history and reproductive strategies, mating strategies, foraging strategies, and how ecological factors drive these relationships. I also conduct field research to better model the behavior of these virtual organisms. Here I am pictured with an adult male gelada in Ethiopia!
I specialize in writing agent-based models for both research in and the teaching of subjects including: biology, genetics, evolution, demography, and behavior.
For my dissertation research, I have developed “B3GET,” an agent-based model which simulates populations of virtual organisms evolving over generations, whose evolutionary outcomes reflect the selection pressures of their environment. The model simulates several factors considered important in biology, including life history trade-offs, investment in body size, variation in aggression, sperm competition, infanticide, and competition over access to food and mates. B3GET calculates each agent’s ‘decision-vectors’ from its diploid chromosomes and current environmental context. These decision-vectors dictate movement, body growth, desire to mate and eat, and other agent actions. Chromosomes are modified during recombination and mutation, resulting in behavioral strategies that evolve over generations. Rather than impose model parameters based on a priori assumptions, I have used an experimental evolution procedure to evolve traits that enabled populations to persist. Seeding a succession of populations with the longest surviving genotype from each run resulted in the evolution of populations that persisted indefinitely. I designed B3GET for my dissertation, but it has an indefinite number of applications for other projects in biology. B3GET helps answer fundamental questions in evolutionary biology by offering users a virtual field site to precisely track the evolution of organismal populations. Researchers can use B3GET to: (1) investigate how populations vary in response to ecological pressures; (2) trace evolutionary histories over indefinite time scales and generations; (3) track an individual for every moment of their life from conception to post-mortem decay; and (4) create virtual analogues of living species, including primates like baboons and chimpanzees, to answer species-specific questions. Users are able to save, edit, and import population and genotype files, offering an array of possibilities for creating controlled biological experiments.
Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).
The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.
I received my BSc, MSc, and PhD from the University of Nottingham. My PhD focuses on the Agent-Based Modelling and Simulation (ABMS) of Public Goods Game (PGG) in Economics. In my thesis, a development framework was developed using software-engineering methods to provide a structured approach to the development process of agent-based social simulations. Also as a case study, the framework was used to design and implement a simulation of PGG in the continuous-time setting which is rarely considered in Economics.
In 2017, I joined international, inter-disciplinary project CASCADE (Calibrated Agent Simulations for Combined Analysis of Drinking Etiologies) to further pursue my research interest in strategic modelling and simulation of human-centred complex systems. CASCADE, funded by the US National Institutes of Health (NIH), aims to develop agent-based models and systems-based models of the UK and US populations for the sequential and linked purposes of testing theories of alcohol use behaviors, predicting population alcohol use patterns, predicting population-level alcohol outcomes and evaluating the impacts of policy interventions on alcohol use patterns and harmful outcomes.
Dr. Lilian Alessa, University of Idaho President’s Professor of Resilient Landscapes in the Landscape Architecture program, is also Co-Director of the University of Idaho Center for Resilient Communities. She conducts extensive research on human adaptation to environmental change through resilient design at landscape scales. Much of her work is funded by the National Science Foundation, including projects awarded the Arctic Observing Network, Intersections of Food, Energy and Water Systems (INFEWS) and the Dynamics of Coupled Natural Human Systems programs. Canadian-born and raised, Alessa received her degrees from the University of British Columbia. She also uses her expertise in social-ecological and technological systems science to develop ways to improve domestic resource security for community well-being, particularly through the incorporation of place-based knowledge. Her work through the Department of Homeland Security’s Center of Excellence, the Arctic Domain Awareness Center, involves developing social-technological methods to monitor and respond to critical environmental changes. Lil is a member of the National Science Foundation’s Advisory Committee for Environmental Research and Education and is on the Science, Technology and Education Advisory Committee for the National Ecological Observing Network (NEON). Professor Alessa also teaches a university landscape architecture capstone course: Resilient Landscapes with Professor Andrew Kliskey. Professor Alessa’s collaborative grant activity with Professor Andrew Kliskey, since coming to the university in 2013, exceeds 7 million USD to date. She has authored over a 100 publications and reports and has led the development of 2 federal climate resilience toolbox assessments, the Arctic Water Resources Vulnerability Index (AWRVI) and the Arctic Adaptation Exchange Portal (AAEP).