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Evaluating the coherence of Take-the-best in structured environments

Creative Commons 'BY' version 4.0 license

Heuristic decision-making models, like take-the-best, rely on environmental regularities. They conduct a limited search, and ignore available information, by assuming there is structure in the decision-making environment. Take-the-best relies on at least two regularities: diminishing returns, which says that information found earlier in search is more important than information found later; and correlated information, which says that information found early in search is predictive of information found later. We develop new approaches to determining search orders, and to measuring cue discriminability, that make the reliance of take-the-best on these regularities clear, and open to manipulation. We then demonstrate, in the well-studied German cities environment, and three new city environments, when and how these regularities support take-the-best. To do this, we focus not on the accuracy of take-the-best, as most previous studies have, but on a measure of its coherence as a decision-making process. In particular, we consider whether take-the-best decisions, based on a single piece of information, can be justified because an exhaustive search for information is unlikely to yield a different decision. Using this measure, we show that when the two environmental regularities are present, the decisions made by limited search are unlikely to have changed after exhaustive search, but that both regularities may be necessary.

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