Computational modelling has a rich history of successful use in researching cognitive phenomena. Its discoveries and applications do not seem to be stopping, yet with the rise of contemporary cognitive science paradigms, its scope and limits have been consistently put into the spotlight. The article reveals the scope of computational modelling by revealing its important role in progressing cognitive science research and helping cause important paradigm shifts as well as being useful at many levels of analysis. The limits are revealed to be some that are not easily solvable, if at all, mostly as they are not dependant on technological advancements. There are two main obstacles for computational modelling of cognitive phenomena: research bias, which manifests through the necessary presence of the designer's epistemological position as well as ideas on the mind and thus unavoidably being included in the model; and autonomy, the impenetrable basic element of living nature, which seems to make living organisms self-determine and thus create their own meaning in the world, something that seems to be unmodellable due to the designer always inputting her own meanings into the model and onto the modelled agents, which has been dubbed the PacMan Syndrome. Computational modelling is discussed in the light of these shortcomings, especially what it means to model living nature.

KEY WORDS
cognitive science paradigms, computational modelling, history of cognitive science, PacMan Syndrome, research bias

CLASSIFICATION

ACM:	I.2.0
JEL:	D91