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Leigh Tesfatsion received the Ph.D. degree in economics from the University of Minnesota, Mpls., in 1975, with a minor in mathematics. She is Research Professor of Economics, Professor Emerita of Economics, and Courtesy Research Professor of Electrical & Computer Engineering, all at Iowa State University. Her principal current research areas are electric power market design and the development of Agent-based Computational Economics (ACE) platforms for the performance testing of these designs. She is the recipient of the 2020 David A. Kendrick Distinguished Service Award from the Society for Computational Economics (SCE) and an IEEE Senior Member. She has served as guest editor and associate editor for a number of journals, including the IEEE Transactions on Power Systems, the IEEE Transactions on Evolutionary Computation, the Journal of Energy Markets, the Journal of Economic Dynamics and Control, the Journal of Public Economic Theory, and Computational Economics. Online Short Bio
Agent-based computational economics (ACE); development and use of ACE test beds for the study of electric power market operations; development and use of ACE test beds for the study of water, energy, and climate change
I have developed several agent-based and cellular automata applications combining agent-based modelling, geographical information systems and visualisation to understand the complex mechanisms of decision making in land use change and environmental stewardship in order to analyse:
• the role of pastoral agriculture in regional development,
• the tradeoffs between land use intensification and water quality,
• the adoption of land-based climate change mitigation practices, and
• the incorporation of cultural values into spatial futures or scenario modelling.
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 work centers on evaluating the adaptiva capacity and proposing strategies for managing forest under climate change in both temperate and tropical areas.
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}).
I have a BS in Earth Sciences and a PhD in Resource and Environmental Economics. I have more than 25 years of experience doing research and teaching and advising students in systems thinking, scenario development, simulation, and ecological economics. Presently, I am an Associate Professor in the Department of Computational & Data Sciences at George Mason University, and a member of the Center for Social Complexity. I teach the introductory courses on Computational Social Sciences at both the undergraduate and graduate levels, as well as beginning and advanced courses in complex systems, modeling, and simulation. My current research focuses on the use of scenario development and integrated modeling as applied to social-ecological systems. My recent work has focused on applying these to issues related to climate change economics and policy, including new technologies for greenhouse gas removal and solar radiation management.
Improving agent models and architectures for agent-based modelling and simulation applied to crisis management. In particular modelling of BDI agents, emotions, cognitive biases, social attachment, etc.
Designing serious games to increase awareness about climate change or natural disasters; to improve civil engagement in sustainable urban planning; to teach Artificial Intelligence to the general public; to explain social phenomena (voting procedures; sanitary policies; etc).
Topics:
Behavioural aspects of environmental problems: Use of evolutionary approaches to investigate how people react to environmental policy.
Resource scarcity
Climate-economic Models: Understand how economic agents think and decide about climate change and climate protection
Sustainable Development
Methods:
Agent-Based-Modeling
Genetic algorithms
Evolutionary economics
Behavioural economics
Ecological economics
Complexity Theory
Garry Sotnik is a lecturer at the Stanford Doerr School of Sustainability, teaching human adaptation to climate change, decision-making, and transformative social change.
complexity, agent-based modeling, cognition
Displaying 10 of 23 results Climate Change clear search