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A common practice in cognitive modeling is to develop new models specific to each particular task. We question this approach and draw on an existing theory, instance-based learning theory (IBLT), to explain learning behavior in three different choice tasks. The same instance-based learning model generalizes accurately to choices in a repeated binary choice(More)
In decisions from experience, there are 2 experimental paradigms: sampling and repeated-choice. In the sampling paradigm, participants sample between 2 options as many times as they want (i.e., the stopping point is variable), observe the outcome with no real consequences each time, and finally select 1 of the 2 options that cause them to earn or lose(More)
In this paper, we show how participants learn to control a simple dynamic stocks and flows task with repeated inflow and outflow decisions. We present the effect that environmental inflow functions of different slopes (positive and negative) have on our ability to control the simple dynamic system. We investigate this slope effect in two experiments with(More)
This research tests people's support for the ''wait-and-see'' approach in climate change due to the uncertainty in both the timing and probability of future consequences. In a laboratory experiment, carbon-tax consequences were presented to participants in one of two forms: a written description, where the probability, consequences, and timing were(More)
Three experiments simulating military RADAR detection addressed a training difficulty hypothesis (training with difficulty promotes superior later testing performance) and a procedural reinstatement hypothesis (test performance improves when training conditions match test conditions). Training and testing were separated by 1 week. Participants detected(More)
This paper presents a case of parsimony and generalization in model comparisons. We submitted two versions of the same cognitive model to the Market Entry Competition (MEC), which involved four-person and two-alternative (enter or stay out) games. Our model was designed according to the Instance-Based Learning Theory (IBLT). The two versions of the model(More)
This paper presents a cognitive model of stimulus-response compatibility (SRC) effects for a situation in which location-relevant and location-irrelevant tasks are intermixed within a single trial block. We provide a computational explanation of the cognitive processing involved in the mixed-task condition. The model is based on the Instance-Based Learning(More)
In a corporate network, the situation awareness (SA) of a security analyst is of particular interest. A security analyst is in charge of observing the online operations of a corporate network (e.g., an online retail company with an external webserver and an internal fileserver) from threats of random or organized cyber-attacks. The current work describes a(More)
Binary-choice reactions are typically faster when the stimulus location corresponds with that of the response than when it does not. This advantage of spatial correspondence is known as the stimulus-response compatibility (SRC) effect when the mapping of stimulus location, as the relevant stimulus dimension, is varied to be compatible or incompatible with(More)