TY - GEN
T1 - Steady-state distributions for human decisions in two-alternative choice tasks
AU - Stewart, Andrew
AU - Cao, Ming
AU - Leonard, Naomi Ehrich
PY - 2010
Y1 - 2010
N2 - In human-in-the-loop systems, humans are often faced with making repeated choices among finite alternatives in response to observations of the evolving system performance. In order to design humans into such systems, it is important to develop a systematic description of human decision making in this context. We examine a commonly used, drift-diffusion, decision-making model that has been fit to human neural and behavioral data in sequential, two-alternative, forced-choice tasks. We show how this model and type of task together can be regarded as a Markov process, and we derive the steady-state probability distribution for choice sequences. Using the analytic expression for this distribution, we prove matching behavior for tasks that exhibit a matching point and we compute the sensitivity of steady-state choices to a model parameter that measures the decision maker's "exploratory" tendency.
AB - In human-in-the-loop systems, humans are often faced with making repeated choices among finite alternatives in response to observations of the evolving system performance. In order to design humans into such systems, it is important to develop a systematic description of human decision making in this context. We examine a commonly used, drift-diffusion, decision-making model that has been fit to human neural and behavioral data in sequential, two-alternative, forced-choice tasks. We show how this model and type of task together can be regarded as a Markov process, and we derive the steady-state probability distribution for choice sequences. Using the analytic expression for this distribution, we prove matching behavior for tasks that exhibit a matching point and we compute the sensitivity of steady-state choices to a model parameter that measures the decision maker's "exploratory" tendency.
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U2 - 10.1109/acc.2010.5530563
DO - 10.1109/acc.2010.5530563
M3 - Conference contribution
AN - SCOPUS:77957795749
SN - 9781424474264
T3 - Proceedings of the 2010 American Control Conference, ACC 2010
SP - 2378
EP - 2383
BT - Proceedings of the 2010 American Control Conference, ACC 2010
PB - IEEE Computer Society
ER -