I am a senior lecturer teaching integrated water resources management at the department of Agricultural Engineering of University of Dschang Cameroon, holding a PhD in Applied development Sciences.
I am interested in network theory of change and agent-based. modeling.
I am currently working as a researcher engineer at the Trustworthy, Intelligent, Self-organizing Information Systems Laboratory (LICIA) of the French Alternative Energies and Atomic Energy Commission (CEA) since January 2017, where I carry out research in distributed problem solving in general.
I am interested in working on open interdisciplinary problems in domains like multi-agent systems, collective intelligence, self-organization and self-adaptation, biological systems, distributed clock synchronization and behavioural economics.
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
To understand the nature of sustainable biophysical/economic systems. To determine the necessary and sufficient conditions for sustainability. To explore the trade-off between sustainability and social or economic justice. To investigate the application of the MEP and/or the MEPP to economic systems, or agent-based models of economic systems.
Integrating social and natural science to study coupled human-natural systems, and particularly the interactions of society with the physical environment under conditions of environmental stress.
Fabian Adelt graduated in computer-sciences with a minor in sociology of technology (degree: Diplom-Informatiker) at TU Dortmund University in 2011. Currently, he is research fellow at the Technology Studies Group and involved in the project “Collaborative Data- and Risk-Management in Future Grids – A Simulation Study” (KoRiSim). Between 2012 and 2015 he worked on the project “Mixed Modes of Governance as a Means of Risk Management in Complex Systems” (RiskSim). His research interests entail agent-based modelling and simulating of socio-technical systems, especially focussing on governance issues and actors’ reactions on interventions. Experience covers the fields of mobility and energy.
Intrapreneur and experienced Consultant with a demonstrated history in the energy industry. Skilled in Business Planning, Corporate Finance, Digital Transformation and Analytics. Strong consulting professional focused in Organizational Development and Project Management. I have a degree in Industrial Engineering from the Rio de Janeiro State University (2000) and a master’s degree in Economics from Brazilian Institute of Capital Markets IBMEC (2003). Has experience in the area of Computer Science, with emphasis on Modeling of Complex Systems.
Complex Systems
Agent-based Models
System Dynamics
Innovation
Economics
Organizational Development
Gary Polhill did a degree in Artificial Intelligence and a PhD in Neural Networks before spending 18 months in industry as a professional programmer. Since 1997 he has been working at the Institute on agent-based modelling of human-natural systems, and has worked on various international and interdisciplinary projects using agent-based modelling to study agricultural systems, lifestyles, and transitions to more sustainable ways of living. In 2016, he was elected President of the European Social Simulation Association, and was The James Hutton Institute’s 2017 Science Challenge Leader on Developing Technical and Social Innovations that Support Sustainable and Resilient Communities.
IRPact - An integrated agent based modeling approach in innovation diffusion
Goal: The goal of IRPact is to develop a flexible and generic innovation-diffusion ABM (agent-based modelling) framework, based on requirements derived from a literature analysis. The aim of IRPact is to allow for modeling a large number of application contexts and questions of interest.
It provides a formal model (framework) as well as a software implementation in order to assist modelers with a basic infrastructure for their own research.
Conceptually it is thought to be part of the IRPsim (https://irpsim.uni-leipzig.de), with the vision to bring together rational approaches and cognitive modeling in an integrated approach within the context of sustainable energy markets.
GARRY SOTNIK is a Lecturer with the Sustainability Science and Practice Program in the School of Earth, Energy and Environmental Sciences. He is a systems scientist with research focused on identifying robust strategies in contexts defined by deep uncertainty and global climate change. Garry develops and implements agent-based computer simulation models that explore co-evolutionary interactions among human cognition and behavior, on the one end, and biophysical conditions, on the other. He has experience designing and teaching courses on agent-based modeling and on different approaches to modeling coupled human and natural systems. Garry holds a Ph.D. in Systems Science from Portland State University and an M.A. in Economics and a B.S. in Management from Boston University.
agent-based modeling, cognition