On the role(s) of modelling in cognitive science

Although work on computational and robotic modelling of cognition is highly diverse, as an empirical method it can be roughly divided into at least two clearly different, though non-exclusive branches, motivated to evaluate the sufficiency or the necessity of theories when it comes to accounting for data and/or other observations. With the rising profile of theories of situated/embodied cognition, a third non-exclusive avenue for investigation has also gained in popularity, the investigation of agent-environment embedding or more generally, exploration. Still in its infancy, and often confused with sufficiency testing, this relatively new kind of modelling, which is theory- rather than data-driven, investigates the role of the environment in shaping the ontogenetic and/or phylogenetic development of situated agency. Each of these three approaches presents many issues that modellers must be sensitive to, both in the design of experiments, and in the conclusions that can be drawn from them. This paper highlights some of these issues, provides examples, and addresses the contribution of computational/robotic modelling to cognitive science, as well as some of its limitations.