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Integrated Water resource management
Integrated coastal management
Complex socio-biophysical modelling
Computational social modelling
Agent-Based modelling
Participatory modelling
System Dynamics modelling
Operations Management Production Planning Optimization Agribusiness Management Agent Based Modeling Complex Systems Biology Agent Based Intelligent Systems Complex Systems Complex Adaptive Systems Complex System Optimization, Optimization-simulation models.
Hi. I’m Wolf. I’m the Argelander (Tenure-Track Assistant) Professor for Integrated System Modeling for Sustainability Transitions at the University of Bonn, Germany.
We reshape human-environment modeling to identify critical leverage points for sustainability transitions.
Cooperation at scale – in which large collectives of intelligent actors in complex environments seek ways to improve their joint well-being – is critical for a sustainable future, yet unresolved.
To move forward with this challenge, we develop a mathematical framework of collective learning, bridging ideas from complex systems science, multi-agent reinforcement learning, and social-ecological resilience.
I am an anthropologist from the Universidad Nacional de Colombia. I am interested in ethnomusicology, art, and complex systems, especially socio-ecological. I want to understand how cultural expressions and social rules are part of a more complex system and how they are intertwined with other non-human behaviors
I am interested in modeling socio-ecological systems. I am currently working on the implementation of a seed-exchange model for understanding the role of some kinship patterns (locality and seed heritage rules) in agrobiodiversity.
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.
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.
Agent based modelling;
Land use/land cover change;
Payment for ecosystem services;
Bayesian Network;
System Dynamics
I am investigating the use of machine learning techniques in non-stationary modeling environments to better reproduce aspects of human learning and decision-making in human-natural system simulations.
Using the Complex System science paradigm to open new ways of assessing the Systemic Risk in Financial Systems
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