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Poster C136 in Poster Session C - Friday, August 9, 2024, 11:15 am – 1:15 pm, Johnson Ice Rink
Modeling Within-Trial Confidence Trajectories of Reasoning using Quantum Random Walk
Ritesh Malaiya1 (), Stacie Warren1, Michael Lundie2, Daniel Krawczyk1, Richard Golden1; 1The University of Texas at Dallas, Richardson, USA, 2Applied Research Associates, Inc., Littleton, USA
In human decision-making, a change-of-mind study analyzes the likelihood of changing the current response choice after conflicting evidence is presented. Several studies have shown that a participant’s confidence state associated with the current response may predict change of mind on subsequent responses. Such studies are limited in that they require explicit confidence ratings, within a trial, which can interfere with the cognitive dynamics of response choice. However, computational models can be used to approximate such within-trial dynamics. The present study tested whether the within-trial change in confidence for an initial response is predictive of change of mind on subsequent responses. Within-trial confidence describes the change in confidence state when a stimulus is presented until a response is elicited. A Quantum Random Walk (QRW) model was applied to estimate the within-trial confidence trajectory using a confirmation bias task's response accuracy and time. Participants with a higher estimated starting confidence state were found less likely to change their subsequent response choice. Across observed confidence groups (increased, decreased, no change) the estimated QRW confidence states significantly differed for easy and hard trials. Also, the estimated within-trial confidence trajectory for the first response significantly correlated with the observed confidence change between the first and second responses. QRW estimates of individuals' within-trial confidence effectively predicted the individuals' observed confidence states. Thus, QRW as applied to reasoning tasks can effectively model individual differences in within trial confidence trajectories.
Keywords: Quantum Random Walk Reasoning Metacognition Bayesian Inference