Community

Cheddi Kiravu Member since: Tuesday, February 09, 2010

Electrical Power Engineering, Science (Physics, Mathematics, and Education)

Network ABMS in solar technology adoption in households

Tom Briggs Member since: Tuesday, December 13, 2016 Full Member Reviewer

MPS, Industrial/Organizational Psychology, BA, Psychology

PhD Student, Computational Social Science
Department of Computational and Data Sciences
George Mason University
Fairfax, VA, USA

I use ABM to study organizations, leadership, employee behavior and performance, and the social/psychological theories addressing workplace behavior and outcomes.

I have also used ABM to explore mass violence, active shooters, and mass shootings, including the spread of mass violence and its antecedents.

Gilberto Camara Member since: Tuesday, January 14, 2014 Full Member Reviewer

PhD

One of my research areas is agent-based modelling of land change in Brazil. I have worked with ABM in frontier areas of the Brazilian Amazon. I am also part of the team that develops TerraME, an OSS toolkit for ABM in cellular spaces.

Jonas Hauke Member since: Friday, September 15, 2017

ABM, Organizational Behaviour, Airport Management

N Perdue Member since: Wednesday, April 13, 2016

Ph.D.

Cognition and ABM

Sandra Bellekom Member since: Friday, December 19, 2014

energy and environmental sciences

Brent Auble Member since: Friday, December 17, 2010

B.S. Computer Science, Lafayette College, MAIS, Computational Social Science, George Mason University

Dissertation: Narrative Generation for Agent-Based Models

Abstract: This dissertation proposes a four-level framework for thinking about having agent-based models (ABM) generate narrative describing their behavior, and then provides examples of models that generate narrative at each of those levels. In addition, “interesting” agents are identified in order to direct the attention of researchers to the narratives most likely to be worth spending their time reviewing. The focus is on developing techniques for generating narrative based on agent actions and behavior, on techniques for generating narrative describing aggregate model behavior, and on techniques for identifying “interesting” agents. Examples of each of these techniques are provided in two different ABMs, Zero-Intelligence Traders (Gode & Sunder, 1993, 1997) and Sugarscape (Epstein & Axtell, 1996).

Ismael Chaile Member since: Wednesday, December 11, 2013 Full Member Reviewer

Ph.D. with research line in Multi-agent systems and Distributed systems (robots, IoT), Master In Science in Micro and Nanoelectronic, Master in General Direcction and Strategic Planning, Electronic Engineer

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).

Arika Ligmann-Zielinska Member since: Tuesday, April 08, 2008 Full Member Reviewer

PhD

I am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).

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