Marcus Buckmann

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Simple decision heuristics are models of human and animal behavior that use few pieces of information—perhaps only a single piece of information—and integrate the pieces in simple ways, for example, by considering them sequentially, one at a time, or by giving them equal weight. It is unknown how quickly these heuristics can be learned from experience. We(More)
The critical step facing every decision maker is when to stop collecting evidence and proceed with the decision act. This is known as the stopping rule. Over the years, several unconnected explanations have been proposed that suggest nonoptimal approaches can account for some of the observable violations of the optimal stopping rule. The current research(More)
The current study tested the quantity and quality of human exploration learning in a virtual environment. Given the everyday experience of humans with physical object exploration, we document substantial practice gains in the time, force, and number of actions needed to classify the structure of virtual chains, marking the joints as revolute, prismatic, or(More)
In this study compared single stopping rules models to the Cast-Net stopping rule model. The Cast-Net model assumes that several stopping rules can be used simultaneously to determine the stopping point to stop information search and to proceed to making a final decision. We analyzed whether the Cast-net model would pay the price for being more complex when(More)
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