Belief updating in decision-variable space: More fine-grained choices attract future ones more strongly

Abstract

When engaged in decision-making tasks, humans are known to create decision variables. Much effort has focused on the cognitive processes involved in forming decision variables. However, there is limited understanding of how decision variables, once formed, are utilized to adapt to the environment. We reason that decision-makers would benefit from updating their belief on decision variables. As one such belief updating, we hypothesize that commitment to a decision limits the range of possible beliefs about decision variables to align with the committed decision. This implies that past decisions not only attract future ones but also exert a greater pull when decisions are made with finer granularity—dubbed “granularity effect.” Here, we present the findings of seven psychophysical experiments that confirm these implications. Further, we offer a unified Bayesian account of the granularity effect, along with previously established decisional history effects, demonstrating how effectively humans leverage their probabilistic inference for adaptation.