https://ogma.newcastle.edu.au/vital/access/ /manager/Index en-au 5 A Bayesian latent mixture model approach to assessing performance in stock-flow reasoning https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34035 Tue 03 Sep 2019 18:22:10 AEST ]]> Now for Sure or Later With a Risk? Modeling Risky Intertemporal Choice as Accumulated Preference https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41031 Thu 21 Jul 2022 12:29:25 AEST ]]> A hierarchical bayesian modeling approach to searching and stopping in multi-attribute judgment https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18394 Sat 24 Mar 2018 07:52:35 AEDT ]]> Probability matching in risky choice: the interplay of feedback and strategy availability https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:28643 maximizing—is present before the first choice is made. These studies have also indicated that maximizing increases when (1) the asymmetry in the availability of matching and maximizing strategies is reduced and (2) normatively irrelevant outcome feedback is provided. In the two experiments reported here, we examined the joint influences of these factors, revealing that strategy availability and outcome feedback operate on different time courses. Both behavioral and modeling results showed that while availability of the maximizing strategy increases the choice of maximizing early during the task, feedback appears to act more slowly to erode misconceptions about the task and to reinforce optimal responding. The results illuminate the interplay between “top-down” identification of choice strategies and “bottom-up” discovery of those strategies via feedback.]]> Sat 24 Mar 2018 07:37:14 AEDT ]]> Two Bayesian tests of the GLOMOsys model https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29831 sys model.]]> Sat 24 Mar 2018 07:32:50 AEDT ]]> Of matchers and maximizers: how competition shapes choice under risk and uncertainty https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23015 matching was optimal; if the opponent was indifferent, probability maximizing was optimal. We observed accurate asymptotic strategy use in both conditions irrespective of the provision of outcome probabilities, suggesting that participants were sensitive to the differences in opponent behavior. An analysis of reinforcement learning models established that computational conceptualizations of opponent behavior are critical to account for the observed divergence in strategy adoption. Our results provide a novel appraisal of probability matching and show how this individually 'irrational' choice phenomenon can be socially adaptive under competition.]]> Sat 24 Mar 2018 07:15:43 AEDT ]]> A quantum of truth? Querying the alternative benchmark for human cognition https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23463 Sat 24 Mar 2018 07:13:01 AEDT ]]> Causal explanation improves judgment under uncertainty, but rarely in a Bayesian way https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34036 Mon 04 Feb 2019 11:46:00 AEDT ]]>