Complexity and evolutionary simulation models in cognitive science Epistemology of synthetic bottom-up simulation modelling Xabier Barandiaran * xabier@barandiaran.net http://barandiaran.net 26–06–03 Abstract In complex adaptive systems, where internal and external non-linear interactions give rise to an emergent functionality, analytic decomposition of component and isolated functional evaluation of them is not a viable methodological practice. More recently, embodied bottom-up synthetic methodological approaches have been proposed to solve this problem. Evolutionary simulation modelling (specifically evolutionary robotics) provides an explicit research methodology in this direction. We argue and illustrate that the scientific relevance of such methodology can be best understood in terms of a double conceptual blending: i) a conceptual blending between structural and functional levels of description embedded in the simulation; and ii) a methodological blending between empirical and theoretical work in scientific research. Simulation models show their scientific value on: reconceptualization of theoretical assumptions; hypothesis generation and proof of concept. We conclude that simulation models are capable of extending our cognitive and epistemological resources to (re)conceptualise scientific domains and to establish causal relations between different levels of description. Keywords Scientific methodology, cognitive science, models, artificial life, simulation of adaptive behaviour, emergence, epistemology, explanation, conceptual blending, metaphors in science * The ideas developed in this paper have being originated in a paper working by Roberto Feltrero and myself. Complete authorship of the present paper shall recognize Roberto’s contribution, specially on conceptual blending literature and fruitfull discussion on the topics involved. 1