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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)
We developed a system dynamics model for a simple, but important stock and flows task where the objective was to control the water level in a tank within an acceptable range of the goal, over a number of time periods, in the presence of an unknown environmental inflow and outflow. We also report how this model accounts for human behavior, using behavioral(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)
OBJECTIVE To determine the effects of an adversary's behavior on the defender's accurate and timely detection of network threats. BACKGROUND Cyber attacks cause major work disruption. It is important to understand how a defender's behavior (experience and tolerance to threats), as well as adversarial behavior (attack strategy), might impact the detection(More)
The use of analogies and repeated feedback might help people learn about the dynamics of climate change. In this paper, we study the influence of repeated feedback on the control of a carbon-dioxide (CO2) concentration to a goal level in a Dynamic Climate Change Simulator (DCCS) using the “bathtub” analogy. DCCS is a simplification of the complex climate(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)