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Open system model of choice and response time

Mr. Gunnar Epping
Indiana University Bloomington ~ Cognitive Science and Psychology
Dr. Peter Kvam
University of Florida ~ Department of Psychology
Tim Pleskac
Indiana University ~ Psychological and Brain Sciences
Dr. Jerome Busemeyer
Indiana University ~ Department of Psychological and Brain Sciences

Sequential sampling models have provided accurate accounts of people’s choice, response time, and preference strength in value-based decision-making tasks. Conventionally, these models are developed as Markov-type processes (such as random walks or diffusion processes) following the Kolmogorov axioms. Quantum probability theory has been proposed as an alternative framework upon which to develop models of cognition, including quantum random walk models. When modeling people’s behavior during decision-making tasks, previous work has demonstrated that both the Markov and quantum models have their respective strengths. Recently, the open system model, which is a hybrid version of the Markov and quantum models, has been shown to provide a more accurate account of preference strength compared to the Markov and quantum models in isolation. In this work, we extend the open system model to make predictions on pairwise choice and response time and compare it to the Markov and quantum random walk models.



Markov random walk
quantum random walk
open system models
preference accumulation
choice behavior
decision time

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Cite this as:

Epping, G. P., Kvam, P., Pleskac, T., & Busemeyer, J. R. (2022, July). Open system model of choice and response time. Paper presented at Virtual MathPsych/ICCM 2022. Via