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Anna Sikora is an Associate Professor in the Computer Architecture and Operating System Department at Autonomous University of Barcelona (UAB).
She got the BS degree in computer science in 1999 from Technical University of Wroclaw (Poland). She got the MSc in computer science in 2001 and in 2004 the PhD in computer science, both from Autonomous University of Barcelona (Spain).
Since 1999 her investigation is related to parallel and distributed computing. Her current main interests are focused on high performance parallel applications, performance models, automatic performance analysis and dynamic tuning. She has been involved in programming tools for automatic and dynamic performance tuning on cluster and Grid environments, as well as in exa-scale systems.
High performance parallel computing, parallel applications, performance models, automatic performance analysis, dynamic tuning. Performance tools for automatic and dynamic performance tuning on HPC systems. Agent-based modelling systems.
I am an agent-based modeller at the James Hutton Institute in Scotland. I specialise in large-scale modelling of social and socio-ecological systems, with a particular focus on simulating stressors and process that could give rise to transformational change. To date, my research has focused on food and agricultural systems, rural economies, and the WASH sector, with much of it informed by firsthand fieldwork in Africa, Asia, and Europe. I am also interested in leveraging open science, participatory research, quantitative ethnography, and grounded theory within modelling processes to collaboratively generate nuanced insights into individual behaviour and societal dynamics. I received the Open Science Award from the International Land Use Study Centre in 2023 for such work. I currently co-lead the European Social Simulation Association’s Special Interest Group on Modelling Transformative Change and I am the Associate Director of the Centre for Empirical Agent-Based Modelling at the James Hutton Institute.
In my research I focus on understanding human behaviour in group(s) as a part of a complex (social) system. My research can be characterised by the overall question: ‘How does group or collective behaviour arise or change given its social and physical context?‘ More specifically, I have engaged with: ‘How is (individual) human behaviour affected by being in a crowd?’, ‘Why do some groups (cooperatively) use their resources sustainably, whereas others do not?‘, ‘What is the role of (often implicit simplistic) assumptions regarding human behaviour for science and/or management?’
To address these questions, I use computational simulations to integrate and reflect synthesised knowledge from literature, empirics and experts. Models, simulation and data analysis are my tools for gaining a deeper understanding of the mechanisms underlying such systems. More specifically, I work with agent-based modelling (ABM), simulation experiments and data analysis of large datasets. Apart from crowd modelling and social-ecological modelling, I also develop methodological tools to analyse social simulation data and combining ABM with other methods, such as behavioural experiments.
Flaminio Squazzoni is Full Professor of Sociology at the Department of Social and Political Sciences of the University of Milan and director of BEHAVE. He teaches “Sociology” to undergraduate students, “Behavioural Sociology” to master students and “Behavioural Game Theory” to PhD students. Untill November 2018, he has been Associate Professor of Economic Sociology at the Department of Economics and Management of the University of Brescia, where he led the GECS-Research Group on Experimental and Computational Sociology.
He is editor of JASSS-Journal of Artificial Societies and Social Simulation, co-editor of Sociologica -International Journal for Sociological Debate and member of the editorial boards of Research Integrity and Peer Review and Sistemi Intelligenti. He is advisory editor of the Wiley Series in Computational and Quantitative Social Science and the Springer Series in Computational Social Science and member of the advisory board of ING’s ThinkForward Initiative. He is former President of the European Social Simulation Association (Sept 2012/Sept 2016, since 2010 member of the Management Committee) and former Director of the NASP ESLS PhD Programme in Economic Sociology and Labour Studies (2015-2016).
His fields of research are behavioural sociology, economic sociology and sociology of science, with a particular interest on the effect of social norms and institutions on cooperation in decentralised, large-scale social systems. His research has a methodological focus, which lies in the intersection of experimental (lab) and computational (agent-based modelling) research.
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).
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).
Gerd Wagner is Professor of Internet Technology at Brandenburg University of Technology, Cottbus, Germany. After studying Mathematics, Philosophy and Informatics in Heidelberg, San Francisco and Berlin, he (1) investigated the semantics of negation in knowledge representation formalisms, (2) developed concepts and techniques for agent-oriented modeling and simulation, (3) participated in the development of a foundational ontology for conceptual modeling, the Unified Foundational Ontology (UFO), and (4) created a new Discrete Event Simulation paradigm, Object Event Modeling and Simulation (OEM&S), and a new process modeling language, the Discrete Event Process Modeling Notation (DPMN). Much of his recent work on OEM&S and DPMN is available from sim4edu.com.
Modeling and simulation of agents and other discrete systems.
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