The newly emerging school of economics called "evolutionary economics" challenges most mainstream approaches in the field by insisting that most, if not all economic phenomena have to be viewed as non-linear, disequilibrium dynamics. Moreover the evolutionary approach suggests that a useful description of economic systems has to incorporate the emergence of new elements of the economic process - of technical and social innovations as well as of new knowledge. To do so, it sometimes stresses similarities to biology, using the metaphor of "mutation and test" as a guiding principle for modeling. Evidently these high aspirations call for the most advanced formal methods. As a newly emerging field of research it falls itself under the category of a wide innovative variety of models that are going to be tested for their usefulness in the near future. Our research group at ZiF aims at exploring three particularly important and flourishing directions within evolutionary economics:
The methodological position of the evolutionary approach
Locating the particular features of the approach - in its historical and formal dimensions - is still one of the hottest debated issues in evolutionary economics. Does it lead to a broader formal (simulation) language?
Evolutionary game theory and the emergence of norms
Game theory has been contributing to the evolutionary approach from its very start. It forces model-builders to make precise assumptions on - possibly distorted - information processing of players. More recently the emergence of norms in game-theoretic simulation environments shed new light on the emergence of institutions. How do norms emerge and why do they vanish again?
Genetic algorithms and learning
In the last decade there has been an upsurge of economic models using genetic algorithms. Indeed the notion of learning starts to occupy a central role in socio-economic reasoning. Though there are analogies to biology, the startling question is, if and how genetic algorithms are particularly suitable to formalize human social learning.
Of course, these topics are closely linked to each other. And there is justified hope that exchanging ideas with experts in different scientific areas using similar formal tools will lead to mutual intellectual benefits.