Inspirational anchors: minimal computational models in cognitive science

Abstract

In model-based science, a minimal computational model (MCM) is a computational model developed without the guidance of significant empirical evidence about the mechanism being modelled. Despite their historical and contemporary prominence in cognitive science, MCMs face serious challenges: (1) because of the lack of empirical grounding, it is hard to see how we are justified in making inferences from a model to its target and (2) if they say nothing about their targets, it seems that their utility is limited to the articulation of mere logical possibilities. In this article, I scrutinise this challenge by surveying and rejecting some alternative accounts of the epistemological role of MCMs. I argue that these models are best viewed as fulcra upon which additional research is leveraged. In support, I draw connections between cognitive and economic modelling, and sketch how a prominent account of the latter can be extended to cover the former.