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  1. Insight and strategy in multiple-cue learning.David R. Shanks - 2006 - Journal of Experimental Psychology: General 135 (2):162-183.
    Insight and strategy 2 Abstract In multiple-cue learning (also known as probabilistic category learning) people acquire information about cue-outcome relations and combine these into predictions or judgments. Previous studies claim that people can achieve high levels of performance without explicit knowledge of the task structure or insight into their own judgment policies. It has also been argued that people use a variety of suboptimal strategies to solve such tasks. In three experiments we re-examined these conclusions by introducing novel measures of (...)
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  • Simple Threshold Rules Solve Explore/Exploit Trade‐offs in a Resource Accumulation Search Task.Ke Sang, Peter M. Todd, Robert L. Goldstone & Thomas T. Hills - 2020 - Cognitive Science 44 (2):e12817.
    How, and how well, do people switch between exploration and exploitation to search for and accumulate resources? We study the decision processes underlying such exploration/exploitation trade‐offs using a novel card selection task that captures the common situation of searching among multiple resources (e.g., jobs) that can be exploited without depleting. With experience, participants learn to switch appropriately between exploration and exploitation and approach optimal performance. We model participants' behavior on this task with random, threshold, and sampling strategies, and find that (...)
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  • Probability matching in choice under uncertainty: Intuition versus deliberation.Derek J. Koehler & Greta James - 2009 - Cognition 113 (1):123-127.
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  • Experiential Limitation in Judgment and Decision.Ulrike Hahn - 2014 - Topics in Cognitive Science 6 (2):229-244.
    The statistics of small samples are often quite different from those of large samples, and this needs to be taken into account in assessing the rationality of human behavior. Specifically, in evaluating human responses to environmental statistics, it is the effective environment that matters; that is, the environment actually experienced by the agent needs to be considered, not simply long‐run frequencies. Significant deviations from long‐run statistics may arise through experiential limitations of the agent that stem from resource constraints and/or information‐processing (...)
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  • Understanding repeated simple choices.Iddo Gal - 1996 - Thinking and Reasoning 2 (1):81 – 98.
    This study examined students' reasoning about simple repeated choices. Each choice involved ''betting'' on two events, differing in probability. We asked subjects to generate or evaluate alternative strategies such as betting on the most likely event on every trial, betting on it on almost every trial, or employing a ''probability matching'' strategy. Almost half of the college students did not generate or rank strategies according to their expected value, but few subjects preferred a strategy of strict probability matching. High-school students (...)
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  • Made to measure: Ecological rationality in structured environments. [REVIEW]Seth Bullock & Peter M. Todd - 1999 - Minds and Machines 9 (4):497-541.
    A working assumption that processes of natural and cultural evolution have tailored the mind to fit the demands and structure of its environment begs the question: how are we to characterize the structure of cognitive environments? Decision problems faced by real organisms are not like simple multiple-choice examination papers. For example, some individual problems may occur much more frequently than others, whilst some may carry much more weight than others. Such considerations are not taken into account when (i) the performance (...)
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