Proceedings of the Annual Meeting of the Cognitive Science Society

Human rationality is predominantly evaluated by the extent to which the mind respects the tenets of normative formalismslike logic and probability theory, and is often invoked by appealing to the notion of optimality. Drawing on bounded ratio-nality, there has been a surge in the understanding of human rationality with respect to the mind’s limited computationaland cognitive resources. In this work, we focus on a fairly underappreciated, yet crucial, facet of rationality, robustness:insensitivity of a model’s performance to miscalculations of its parameters. We argue that an integrative pursuit of threefacets (optimality, efficient use of limited resources, and robustness) would be a fruitful approach to understanding humanrationality. We present several novel formalizations of robustness and discuss a recently proposed metacognitively-rationalmodel of risky choice (Nobandegani et al., 2018) which is surprisingly robust to under- and over-estimation of its focalparameter, nicely accounting for well-known framing effects in human decision-making under risk.