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Simple heuristics for modeling people's preferential choice had been investigated for some time before the research program represented in this book was launched (e.g., Luce, 1956; Payne, Bettman, & Johnson, 1993; Tversky, 1969, 1972). The common explanation for people's reliance on these heuristics centered on accuracy–effort trade-offs; that is, the importance that a person places on making an accurate decision versus saving cognitive effort. At its outset, the fast-and-frugal heuristics program focused on inference rather than on preference (see Chapter 2). The reason was that the program dispensed with the previous focus on coherence criteria (e.g., the laws of probability or the axioms of expected utility theory) and conceptualized heuristics as tools for adaptive and accurate decision making in the real world. But to demonstrate the accuracy of heuristics, one needs a clear and accepted benchmark. With respect to preference, accuracy of choice has been defined in many ways, ranging from coherence (e.g., transitivity) to “gold standards,” such as the expected utility model or expected value model. Inference, in contrast, comes with the advantage of external criteria, thus enabling a clear-cut definition of accuracy. By looking at these external criteria, the research program could demonstrate that trading accuracy for effort is not the whole story. Less effort in terms of less information, time, and computation can actually lead to higher accuracy.
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