The area has its roots in complex systems and ideas on emergent phenomena generated by underlying mechanisms. This includes models and methods that use processes of learning and evolution as well as models that can be described as agent-based. The latter means that one explicitly includes model components that capture individual decision processes and how these depend on behaviour of other agents and the system properties.
Parts of this research connect strongly to our research in energy and environment. Studies of the turnover of resources and energy in society are often based on optimisation as a method for characterising possible paths of development. By instead using an approach that builds on agent-based modelling, the ambition is to relax some assumptions on ideal system properties, like perfect information, in order to get complementary perspectives on possibilities and problems in, for example, the transition of the energy system towards renewable energy.
Kristian Lindgren, Claes Andersson, Christian Azar, Daniel Johansson
Liv Lundberg, Emma Jonson, Kristian Lindgren, David Bryngelsson, Vilhelm Verendel. A cobweb model of land-use competition between food and bioenergy crops, Journal of Economic Dynamics and Control 53, 1-14 (2015).
Kristian Lindgren, Emma Jonson, and Liv Lundberg. Projection of a heterogenous agent-based production economy model to a closed dynamics of aggregate variables,” Advances in Complex Systems 8, 1550012 (2015).
Vilhelm Verendel, Daniel J. A. Johansson, Kristian Lindgren. Strategic reasoning and bargaining in catastrophic climate change games, Nature Climate Change 6 (3), 265-268 (2016).
Emma Jonson, Christian Azar, Kristian Lindgren, Liv Lundberg. Exploring the competition between variable renewable electricity and a carbon-neutral baseload technology, Energy Systems, 1-24 (2018). doi.org/10.1007/s12667-018-0308-6