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My research centers on isolating how and to what extent political institutions themselves shape policy. I use computational modeling (agent-based and simulation) to gain theoretical leverage on the issue. This approach allows me to place groups of actors with given preferences into different institutional settings in order to gauge the effect of the rules of the game on political outcomes. Most of my research examines the ways in which legislative processes affect issues of political economy, such as income redistribution.
Analyzing economic dynamics through game theory and agent based evolutionary models. My research topics go from dynamics of organizations to industrial dynamics, macroeconomic dynamics and economic policy analysis.
My interests are focused on the development of new methodologies capable of exploring the complex relations between time, space and human behavior. Simulation, game theory and spatial analysis are some of the techniques that I use to explore different research questions, from the relation between environment and culture to the evolution of warfare.
I’m also the project manager of Pandora, an open-source ABM platform specifically designed for executing large scale simulations in High-Performance Computing environments.
Andrew J. Collins, Ph.D., is an associate professor at Old Dominion University in the Department of Engineering Management and Systems Engineering. He has a Ph.D. in Operations Research from the University of Southampton, and his undergraduate degree in Mathematics was from the University of Oxford. He has published over 80 peer-review articles. He has been the Principal Investigator on projects funded to the amount of approximately $5 million. Dr. Collins has developed several research simulations including an award-winning investigation into the foreclosure contagion that incorporated social networks.
Agent-based Modeling
Agent-based simulation
Cooperative Game Theory
Behavior modeling
Water scarcity generated by climate change and mismanagement, affects individual at microlevel and the society and the system at a more general level. The research focuses on irrigation system and their robustness and adaptation capacity to uncertainty. In particular it investigates the evolution of farmers interactions and the effectiveness of policies by means of dynamic game theory and incorporate the results into an Agent Based Model to explore farmers emergent behaviors and the role of an agency in defining policies. Early knowledge of individual decision makers could help the agency to design more acceptable solutions.
My research focuses pn the intersection between game theory, social networks, and multi-agent simulations. The objectives of this scientific endeavor are to inform policy makers, generate new technological applications, and bring new insight into human and non-human social behavior. My research focus is on the transformation of cultural conventions, such as signaling and lexical forms, and on many cell models models of stem cell derived clonal colony.
Because the models I analyze are formally defined using game theory and network theory, I am able to approach them with different methods that range from stochastic process analysis to multi-agent simulations.
social simulation, Multiagent Systems, Process Algebra, Game Theory
Exhaustible natural resources
Fishery resources
Network game theory models
Agent-based models
I am a computational archaeologist with a strong background in humanities and social sciences, specialising in simulating socioecological systems from the past.
My main concern has been to tackle meaningful theoretical questions about human behaviour and social institutions and their role in the biosphere, as documented by history and archaeology. My research focuses specifically on how social behaviour reflects long-term historical processes, especially those concerning food systems in past small-scale societies. Among the aspects investigated are competition for land use between sedentary farmers and mobile herders (Angourakis et al. 2014; 2017), cooperation for food storage (Angourakis et al. 2015), origins of agriculture and domestication of plants (Angourakis et al. 2022), the sustainability of subsistence strategies and resilience to climate change (Angourakis et al. 2020, 2022). He has also been actively involved in advancing data science applications in archaeology, such as multivariate statistics on archaeometric data (Angourakis et al. 2018) and the use of computer vision and machine learning to photographs of human remains (Graham et al. 2020).
As a side, but not less important interest, I had the opportunity to learn about video game development and engage with professionals in Creative Industries. In one collaborative initiative, I was able to combine my know-how in both video games and simulation models (\href{https://doi.org/10.1007/978-3-030-92843-8_15}{Szczepanska et al. 2022}).
Dr. Chairi Kiourt is a research associate with the ATHENA - Research and Innovation Centre in Information, Communication and Knowledge Technologies - Xanthi’s Division, multimedia department since 2014. Also, as of December 2017, heis PostDoctoral researcher with the Hellenic Open University, School of Science and Technology, and as of 2018, visiting Lecturer at the Department of Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Greece.
In 2003, he received his BSc degree in Electrical Engineering from the Electrical Engineering Department of the Eastern Macedonia and Thrace Institute of Technology, Greece. He also received an M.Sc. in System Engineering and Management in the specialty area: A. Information and Communication Systems Management from the Democritus University of Thrace, Greece. In 2017, received his PhD in Artificial Intelligence and Software Engineering from the Hellenic Open University. He has participated in several national and European research programs and co- authored to the writing of several scientific publications in international peer-reviewed journals and conferences with judges in the fields of collective artificial intelligence, multi-agent systems, reinforcement learning agents, virtual worlds, virtual museums and gamification.
Game playing multi-agent systems, reinforcement learning, colelctive artificial intelligence, distributed computing systems, virtual worlds, gamification
Displaying 10 of 21 results game clear search