Here you will find an evolving list of researchers around the world who do agent-based modeling or related work. This list is intended as a resource for those interested in discovering people doing interesting research in ABM or related fields in different disciplines. Where ever possible, I try to link a picture of the person, which is directly linked to their website.
Total Researchers Listed on this Page: 31
Hussein Abbass’ research interest in Agent-based Modelling is in the area of Cognitive Engineering, Human Modelling, Competitive environments such as wargaming, and socio-technical environments such as air traffic management.
Mohamed Abouel-Ela has recently begun study for his doctorate on ‘ Social Integration and Workplace Segregation: A Simulation Study’, supervised by Katherine Tyler and Nigel Gilbert. The proposed research aims to study the reciprocal relationship between composition (ethnic, racial and/or religious) of workplaces and integration of social networks of different societal groups, and how they change over time. The research aims to develop a multi-agent simulation model for the process of matching workers to jobs through referral hiring. The model is used to examine a number of questions: How social network structure and composition affect/are affected by composition of workplaces? What is the effect of level of segregation of population’s social network? What is the effect of the structure of job information flow? Firm’s size? And what are the effects of the relative sizes of minority and majority groups. The simulation model is validated against primary empirical data collected from a sample of employers and workers in Egypt. The research is funded by the Ministry of Higher Education, Egypt.
Myriam Abramson’s research on agent-based modeling has focused on coordination strategies of intelligent agents and behavioral modeling. Her research interests include reinforcement learning, game theory and neural networks. She is a computer scientist at the Naval Research Laboratory in Washington, DC.
Lilibeth Acosta-Michlik’s research interests focus on integrated assessment modeling on sustainability and vulnerability in the context of climatic, economic and land use changes using statistical (e.g. cluster, conjoint, logit), fuzzy logic, and agent-based techniques.
Shah Jamal Alam’s research interests include agent-based simulation, social policy design, kinship networks, and the socioeconomic impact of HIV/AIDS
Alessandro Acquisti’s research interests include the overlap of information technology, society, and economics; the economics of privacy and information security; the economics of computers; agent-based modeling, ecommerce, cryptography, anonymity, and electronic voting.
Diana Francisca Adamatti’s research interests include Multiagent Based Simulation (MABS), mainly applied in Natural Resource Management. In Multiagent Systems (MAS) area, she works with computational games and emotions in agents.
Mike Agar’s research focuses on ethnography, language, complexity theory, and the organization from both theoretical and practical points of view. Kurt Lewin provides the motto: There is nothing as practical as a good theory. He also works with the Redfish Group in Santa Fe (www.redfish.com), particularly around the application of a blend of ethnography and computer visualization called “OrgViz,” short for “making the organization visible.
Hyungil Ahn’s research interests include computational models of human behavioral, affective and cognitive decision making; machine learning, human-agent Interaction, computational user experience, computational customer experience; prediction models of customer decisions, prediction market, agent-based computational economics; and neuroeconomics, behavioral economics, consumer psychology.
Petra Ahrweiler’s research focuses on innovation networks, university-industry links, management and policy for emerging technologies, knowledge-intensive Industry architectures, complex social systems, and agent-based smulation.
C. Athena Aktipis’ research focuses on Interactions with the physical and social world and the search for fundamental principles that apply at different levels, from the cells to decision makers. She applies ABM to investigate the evolution and emergence of social behavior in a variety of systems across diverse domains.
Jonathan Alberts’ research interests include computational and mathematical models of cellular processes at the level of cytoskeletal polymers, specifically actin-based motility of L. monocytogenes and the ParM mediated plasmid segregation in some bacteria; and building frameworks to make it easier for others to build these types of computational models.
James Albus’ research interests include computational theory of mind, reference model architecture and a design methodology for intelligent systems, peoples’ capitalism: economics of the robot revolution, the RoboCrane, and autonomous vehicle systems.
Ludmil B. Alexandrov’s research interests include understanding the regulation of DNA transcription the connection between DNA dynamics and transcription; Monte Carlo simulations; Langevin molecular dynamics; Agent Base Modeling; high performance computing; parallel programming; and conceptual design.
Benjamin Allen’s primary research area is evolutionary dynamics. He is interested in how the structure of a population can influence the evolution of social behavior. He hopes to develop a general mathematical approach to this question which can transcend and contextualize results from specific models. He is also also interested in the evolution of mutation rates, and the somatic evolution of cancer. Beyond evolutionary dynamics, has have worked on ways to quantify and measure biodiversity. More generally, he is interested in how information theory can help us understand structure and complexity in physical, social, and biological systems.
Rob Allan’s research interests focus on agent based modelling and simulation as a computationally demanding technique having its origins in discrete event simulation, genetic algorithms and cellular automata. Part of his interests are in developing, evaluating and promoting this powerful technique for simulating dynamic complex systems and observing “emergent” behaviour. See his wiki for continual updates on his research and resources.
Chris Amato’s research interests include artificial intelligence, reasoning under uncertainty, multiagent systems, decision theory, game theory, machine learning, resource-bounded reasoning and operations research.
Frédéric Amblard’s research focuses on agent-based simulation of social systems. He is more particularly interested in agent-based simulation of social network dynamics and social influence (information diffusion, opinion/attitude dynamics,…). As a computer scientist by formation he is interested in providing tools and methods to deal with agent-based models (study their properties, calibration and validation of such models).
Gary An’s research focuses on the utilization of agent-based modeling for multi-scale modeling of acute inflammation. Agent levels include cells and molecules, with the goal of simulating organ—and organism—level behaviors from these generative mechanisms. While the focus of his models have primarily been on the pathophysiology of sepsis and multiple organ failure, in a more general sense he is interested in using agent-based modeling as a means of dynamic knowledge representation to augment the biomedical research process. With respect to acute inflammation, the ubiquitousness of the underlying cellular and molecular mechanisms suggest the application of this methodology to such area as oncogenesis, transplant immunology/rejection, autoimmune disease, wound healing/scarring, atherosclerosis and aging.
Li An’s research interests include: GIScience (e.g., GeoComputation and Spatial Analysis) and its link with landscape ecology; complexity theory and its applications in human-environment interactions; landscape ecology: concepts, methods, and applications in environmental and natural resource conservation and policy-making; methodology of quantitative modeling in land-use/cover, wildlife habitat, and biodiversity dynamics; and population, development, and their environmental effects in relation to human health, natural disaster, and biodiversity dynamics, especially in developing countries.
Alexander R. A. Anderson’s research interests include cancer invasion, evolutionary dynamics, angiogenesis, individual based models, spatial models, multiscale models, and tumour microenvironments.
David Andre is a scientist, an inventor, and an entrepreneur whose work emphasizes the role of learning. He is Chief Technical Officer for Cerebellum Capital, Inc, where he is building a black-box that predicts the markets. He is also a research consultant for BodyMedia, Inc. Until recently, he was Director of Research at BodyMedia, where he and his team collected and analyzed clinical and user data and used a variety of machine learning methods to develop algorithms that provide detailed and specific statements about human physiology and activity. His team collected what is perhaps the world’s largest physiological database – approximately 2 million minutes per day, and this rate is increasing exponentially. Additionally, David continues to work on methods for automated program and agent design including various forms of reinforcement learning. He earned bachelors degrees from Stanford University and a Ph.D in AI from Berkeley, where he was awarded a Hertz Fellowship. David also has co-founded several companies, including Blue Pumpkin Software, which makes workforce management software, and Just Passing Through, a company that creates and films multi-day puzzle adventures.
Peter Andreae’s research interests include machine learning, particularly learning from complex structured information. His longstanding interest is in intelligent agents that learn within richly structured worlds, generalise from past experience, and have novel exploratory behaviours. He has done various projects in the area of clustering algorithms, including applications in bioinformatics, web search, and clustering logs of internet attacks.
Giulia Andrighetto received her Ph.D in Philosophy at the University of Rome. She is a post doc at the Laboratory on Agent Based Social Simulationin Institute of Cognitive Sciences and Technologies (ISTC-CNR). Her research aims to develop interdisciplinary studies in the cognitive and social fields. She is interested in applying agent-based social simulation and agent theory to understand emergence and evolution of macro social phenomena in social systems, such as social norms and enforcement institutions.
Simon Angus’ research interests include complexity science, networks, game theory, computational economics, agent-based social simulation, and artificial life.
Luis Antunes’ research interests include distributed artificial intelligence, multi-agent systems, social architectures, decision and motivation in multi-agent systems, social simulation with self-motivated agents, methodologies for exploratory simulation.
David Anzola holds a degree in sociology from the Universidad del Rosario in Bogotá, Colombia. In his thesis he used artificial neural networks to analyze the problem of cultural transmission. He was a lecturer in several subjects of computational modeling and sociological theory and also worked in research projects using ABM’s to analyze the dynamics of strategic sectors. In his PhD he’ll study some epistemological aspects of computational sociology, related mainly with explanation in social simulation.
Babak Mahdavi Ardestani is currently working on a multi-disciplinary project which involves research, design and development of an agent-based complex adaptive system framework for investigating electricity system and smart grid concept. His previous modelling work focused on building an empirically informed hybrid simulation model for investigating residential segregation. Babak’s research interests include Geographically Referenced Social Simulation, Simulation Modelling of Geographical Phenomena, Empirical Validation of Models, Agent-based Computational Economics and Simulation Modelling Methodology. More broadly, he is interested in using Agent-based Modelling, Microsimulation, Geosimulation or a hybrid of these approaches as methodology to investigate complex, nonlinear, self-organized and emerging dynamics, including the relationship between micro-world of individual behaviours (i.e. decision-making actors) and the generated macroscopic effects of the macro-world system under study in different domains and the potential that simulation models offer as decision support and policy-informing tools.
Brenna Argall’s research interests lie with robot autonomy and low level motion control, and how machine learning and human feedback may be used to build control algorithms to accomplish motion tasks. She is currently affiliated with the Learning Algorithms and Systems Laboratory at EPFL, and was previously affiliated with the CORAL Research Group while at Carnegie Mellon.
W. Brian Arthur’ research interests include (1) Technology and Innovation: Where do new technologies come from — how exactly does invention work? What constitutes innovation and how is it achieved? Why are certain regions – Cambridge, England in the 1920s and Silicon Valley today – hotbeds of innovation, while others languish? Does technology, like biological life, evolve? And how do new industries and the economy itself, emerge from technologies? (2) A More Realistic Economics: As recent events show, we badly need to reformulate how we understand the economy. He has been involved since its early days in the science of complexity: the science of how patterns and structures self-organize, and my particular interest here has been in creating a more realistic, non-equilibrium version of economics. (3) Increasing Returns: High technology operates under increasing returns, and to the degree modern economies are shifting toward high tech, the different economics of increasing returns alters the character of competition, business culture, and appropriate government policy in these economies.
Robert Axelrod’s research has focused on on the evolution of cooperation and more recently complexity theory (especially agent-based modeling), and international security.
Robert Axtell’s works at the intersection of economics, behavioral game theory, and multi-agent systems computer science. His most recent research attempts to emerge a macroeconomy from tens of millions of interacting agents.
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