Abstract
SUMMARY 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 the belief of decision-variable. As one such belief updating, we hypothesize that a decision commitment restricts the probabilistic belief distribution of decision variable to a range corresponding to that decision. This implies that past decisions not only attract future ones but also exert a greater pull when those decisions are made with finer granularity— dubbed ‘the granularity effect.’ Here, we present the findings of seven psychophysical experiments that confirm these implications. Further, as a unified account of the granularity effect, we offer a Bayesian model. Our work demonstrates how humans leverage the decision-variable to effectively adapt to their surroundings.
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SUMMARY
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 the belief of decision-variable. As one such belief updating, we hypothesize that a decision commitment restricts the probabilistic belief distribution of decision variable to a range corresponding to that decision. This implies that past decisions not only attract future ones but also exert a greater pull when those decisions are made with finer granularity— dubbed ‘the granularity effect.’ Here, we present the findings of seven psychophysical experiments that confirm these implications. Further, as a unified account of the granularity effect, we offer a Bayesian model. Our work demonstrates how humans leverage the decision-variable to effectively adapt to their surroundings.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵✉ e-mail: heeseung1990{at}gmail.com; visionsl{at}snu.ac.kr
we revised analysis method and figures according to the reviewer's comments during a peer review process
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