Ignorance or integration: the cognitive processes underlying choice behavior

The fast‐and‐frugal heuristic framework assumes noncompensatory tools for human preferences (i.e., priority heuristic) and inferences (i.e., take the best heuristic). According to this framework, these heuristics predict choice behavior as well as model the cognitive processes underlying such behavior. The current paper presents two studies that juxtapose predictions derived from these two simple heuristics with alternative predictions derived from compensatory principles. Dependent measures that included reaction time, choice pattern, confidence level, and accuracy were better predicted by compensatory indices than by noncompensatory indices. These findings suggest that people do not rely on limited arguments only, but tend to integrate all acquired information into their choice processes. This tendency was replicated even when the experimental task facilitated the use of noncompensatory principles. We argue that the fast and frugal heuristics can predict the final outcome only under certain conditions, but even in these particular situations they are not applicable to the processes underlying choice behavior. An integrative model for choice behavior is proposed that better represents the data. Copyright © 2009 John Wiley & Sons, Ltd.     

The similarity heuristic

Decision makers often make snap judgments using fast‐and‐frugal decision rules called cognitive heuristics. Research into cognitive heuristics has been divided into two camps. One camp has emphasized the limitations and biases produced by the heuristics; another has focused on the accuracy of heuristics and their ecological validity. In this paper we investigate a heuristic proposed by the first camp, using the methods of the second. We investigate a subset of the representativeness heuristic we call the “similarity” heuristic, whereby decision makers who use it judge the likelihood that an instance is a member of one category rather than another by the degree to which it is similar to others in that category. We provide a mathematical model of the heuristic and test it experimentally in a trinomial environment. In this environment, the similarity heuristic turns out to be a reliable and accurate choice rule and both choice and response time data suggest it is also how choices are made. We conclude with a theoretical discussion of how our work fits in the broader “fast‐and‐frugal” heuristics program, and of the boundary conditions for the similarity heuristic. Copyright © 2009 John Wiley & Sons, Ltd.     

Précis of Simple heuristics that make us smart

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we explore fast and frugal heuristics--simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data--that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program.     

Training fast and frugal heuristics in military decision making

Fast and frugal heuristics have been used to model decision making in applied domains very effectively, suggesting that they could be used to improve applied decision making. We developed a fast and frugal heuristic for infantry decisions using experts from the British Army. This was able to predict around 80% of their decisions using three cues. Next, we examined the benefits of learning to use the fast and frugal heuristic by training junior officers in the British Army to apply the heuristic and assessing their accuracy and mental workload when making decisions. Their performance was compared to a control condition of junior officers who applied standard military decision methods. Participants using the fast and frugal heuristic made decisions as accurately as participants in the control condition, but with reduced mental demand. This demonstrates that fast and frugal heuristics can be learnt and are as effective as analytic decision methods.     

We favor formal models of heuristics rather than lists of loose dichotomies: a reply to Evans and Over

In their comment on Marewski et al. (good judgments do not require complex cognition, 2009) Evans and Over (heuristic thinking and human intelligence: a commentary on Marewski, Gaissmaier and Gigerenzer, 2009) conjectured that heuristics can often lead to biases and are not error free. This is a most surprising critique. The computational models of heuristics we have tested allow for quantitative predictions of how many errors a given heuristic will make, and we and others have measured the amount of error by analysis, computer simulation, and experiment. This is clear progress over simply giving heuristics labels, such as availability, that do not allow for quantitative comparisons of errors. Evans and Over argue that the reason people rely on heuristics is the accuracy-effort trade-off. However, the comparison between heuristics and more effortful strategies, such as multiple regression, has shown that there are many situations in which a heuristic is more accurate with less effort. Finally, we do not see how the fast and frugal heuristics program could benefit from a dual-process framework unless the dual-process framework is made more precise. Instead, the dual-process framework could benefit if its two “black boxes” (Type 1 and Type 2 processes) were substituted by computational models of both heuristics and other processes.     

Psychological plausibility of the theory of probabilistic mental models and the fast and frugal heuristics

The theory of probabilistic mental models (PMM; G. Gigerenzer, U. Hoffrage, & H. Kleinb?lting, 1991) has had a major influence on the field of judgment and decision making, with the most recent important modifications to PMM theory being the identification of several fast and frugal heuristics (G. Gigerenzer & D. G. Goldstein, 1996). These heuristics were purported to provide psychologically plausible cognitive process models that describe a variety of judgment behavior. In this article, the authors evaluate the psychological plausibility of the assumptions upon which PMM were built and, consequently, the psychological plausibility of several of the fast and frugal heuristics. The authors argue that many of PMM theory's assumptions are questionable, given available data, and that fast and frugal heuristics are, in fact, psychologically implausible.     

Bailing and jailing the fast and frugal way

Legal decisions such as the decision to bail upon adjourning a case have major consequences for both defendants and society. In the English system, magistrates, most of whom are lay people, are afforded considerable discretion and must work under constraints such as time pressure. Judgment analysis of the bail decision making policies of 81 magistrates from 44 courts throughout England and Wales revealed intra‐ and inter‐magistrate inconsistency in bail decisions, discrepancies between stated and elicited cue use, and high levels of post‐decisional confidence. Furthermore, magistrates' policies were better described and predicted by a fast and frugal model characterized by noncompensatory cue use, than by either of two compensatory integration models. The fast and frugal model portrays a picture of bail decision making that conflicts with the ideal practice as defined by the due process model of justice. We discuss the implications of these findings for judgment and decision making research and criminal justice policy. Copyright © 2001 John Wiley & Sons, Ltd.     

Simple rules for detecting depression

Depressive disorders are major public health issues worldwide. We tested the capacity of a simple lexicographic and noncompensatory fast and frugal tree (FFT) and a simple compensatory unit-weight model to detect depressed mood relative to a complex compensatory logistic regression and a naïve maximization model. The FFT and the two compensatory models were fitted to the Beck Depression Inventory (BDI) score of a representative sample of 1382 young women and cross validated on the women's BDI score approximately 18 months later. Although the FFT on average inspected only approximately one cue, it outperformed the naïve maximization model and performed comparably to the compensatory models. The heavier false alarms were weighted relative to misses, the better the FFT and the unit-weight model performed. We conclude that simple decision tools—which have received relatively little attention in mental health settings so far—might offer a competitive alternative to complex weighted assessment models in this domain.     

Classifying simulated air threats with fast and frugal heuristics

In three experiments, subjects learned to classify simulated aircraft using four probabilistic cues then classified test sets designed to contrast predictions of several compensatory and non-compensatory heuristics. Results indicated that a proportion of subjects appeared to use a non-compensatory fast and frugal heuristic but that significant proportions used less frugal compensatory decision rules. The relative proportions of subjects exhibiting responses consistent with the fast and frugal heuristic versus other decision rules was largely unaffected by manipulations of time pressure and perceived cue uncertainty. An extreme time constraint, however, did result in significant differences in the proportions of subjects who preferred non-compensatory to compensatory decision rules. These results suggest that it is possible to model multi-attribute decision tasks like threat assessment with a fast and frugal heuristic although no single heuristic is a general model for the simulated threat assessment task. Copyright © 2006 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.     

Fast and frugal versus regression models of human judgement

Following Brunswik (1952), social judgement theorists have long relied on regression models to describe both an individual's judgements and the environment about which such judgements are made. However, social judgement theory is not synonymous with these compensatory, static, structural models. We compared the characterisations of physicians' judgements using a regression model with that of a non-compensatory process model (called fast and frugal). We found that both models fit the data equally well. Both models suggest that physicians use few cues, that they disagree among themselves, and that their stated cue use is discrepant with the models' stated cue use. However, the fast and frugal model is easier to convey to physicians and is also more psychologically plausible. Implications for how social judgement theorists conceptualise the process of vicarious functioning are discussed.     

Simple mechanisms for gathering social information

Social contexts are notoriously complex, yet decisions are nevertheless made by using simple strategies. We argue that the concept of fast and frugal heuristics provides a promising framework for understanding how we gather social information to make decisions in social environments. That is, we assume that under limitations of time, energy, and computational resources people use cognitively based shortcuts that rely on information from social environments to solve different types of real problems. We review three successful applications of heuristics to the social arena. We first introduce some commonly faced social inference problems (e.g., selecting a mate or deciding whether to cooperate with someone) and then discuss how individuals can use simple strategies to solve such problems. For each problem, we consider how social environments are structured, and how we take advantage of this structure when using heuristics to make inferences and decisions.     

研究人类使用启发式之五原则(英文)

快速节俭启发式框架假定人们使用一套简捷的决策策略——启发式——进行推理、选择、评价及其他决策。这些启发式策略能顺应任务情境结构中的规律, 利用人类的基本认知能力。正基于此, 启发式成就了适应性行为。本文拟对启发式框架进行回顾, 并简要陈述引导研究者研究人类适应性工具箱的五条原则。我们强调, 启发式模型应(ⅰ)精确界定(ⅱ)对照检验(ⅲ)与策略选择理论相符(ⅳ)能评估其对新资料的预测力(ⅴ)能既在实验室又在现实世界中得以检验。     

Coherence shifts in probabilistic inference tasks

The fast‐and‐frugal heuristics approach to probabilistic inference assumes that individuals often employ simple heuristics to integrate cue information that commonly function in a non‐reciprocal fashion. Specifically, the subjective validity of a certain cue remains stable during the application of a heuristic and is not changed by the presence or absence of another cue. The parallel constraint satisfaction (PCS) model, in contrast, predicts that information is processed in a reciprocal fashion. Specifically, it assumes that subjective cue validities interactively affect each other and are modified to coherently support the favored choice. Corresponding to the model's simulation, we predicted the direction and the size of such coherence shifts. Cue validities were measured before, after (Experiment 1), and during judgment (Experiments 2 and 3). Coherence shifts were found in environments involving real‐world cue knowledge (weather forecasts) and in a domain for which the application of fast‐and‐frugal heuristics has been demonstrated (city‐size tasks). The results indicate that subjective cue validities are not fixed parameters, but that they are interactively changed to form coherent representations of the task. Copyright © 2009 John Wiley & Sons, Ltd.     

Heuristic thinking and human intelligence: a commentary on Marewski,Gaissmaier and Gigerenzer

Marewski, Gaissmaier and Gigerenzer (2009) present a review of research on fast and frugal heuristics, arguing that complex problems are best solved by simple heuristics, rather than the application of knowledge and logical reasoning. We argue that the case for such heuristics is overrated. First, we point out that heuristics can often lead to biases as well as effective responding. Second, we show that the application of logical reasoning can be both necessary and relatively simple. Finally, we argue that the evidence for a logical reasoning system that co-exists with simpler heuristic forms of thinking is overwhelming. Not only is it implausible a priori that we would have evolved such a system that is of no use to us, but extensive evidence from the literature on dual processing in reasoning and judgement shows that many problems can only be solved when this form of reasoning is used to inhibit and override heuristic thinking.     

快速节俭启发式--基于有限理性和生态理性的简单决策规则

本文阐述了德国“马克斯．普朗克人类发展研究所”以Gerd Gigerenzer教授为代表的“适应行为与认知中心”简称“ABC研究中心(组)”关于判断、推理和决策制定简单启发式研究的理论背景、研究思路和技术路线,着重介绍了该研究中心在有限理性和生态理性假设基础上提出的一系列极富创意的快速节俭启发式规则,并对围绕这些简单决策规则开展的研究活动作了简要介绍。     

Assessing the empirical validity of the "take-the-best" heuristic as a model of human probabilistic inference

The boundedly rational 'Take-The-Best" heuristic (TTB) was proposed by G. Gigerenzer, U. Hoffrage, and H. Kleinb?lting (1991) as a model of fast and frugal probabilistic inferences. Although the simple lexicographic rule proved to be successful in computer simulations, direct empirical demonstrations of its adequacy as a psychological model are lacking because of several methodical problems. In 4 experiments with a total of 210 participants, this question was addressed. Whereas Experiment 1 showed that TTB is not valid as a universal hypothesis about probabilistic inferences, up to 28% of participants in Experiment 2 and 53% of participants in Experiment 3 were classified as TTB users. Experiment 4 revealed that investment costs for information seem to be a relevant factor leading participants to switch to a noncompensatory TTB strategy. The observed individual differences in strategy use imply the recommendation of an idiographic approach to decision-making research.     

Fast and frugal heuristics are plausible models of cognition: reply to Dougherty, Franco-Watkins, and Thomas (2008)

M. R. Dougherty, A. M. Franco-Watkins, and R. Thomas (2008) conjectured that fast and frugal heuristics need an automatic frequency counter for ordering cues. In fact, only a few heuristics order cues, and these orderings can arise from evolutionary, social, or individual learning, none of which requires automatic frequency counting. The idea that cue validities cannot be computed because memory does not encode missing information is misinformed; it implies that measures of co-occurrence are incomputable and would invalidate most theories of cue learning. They also questioned the recognition heuristic's psychological plausibility on the basis of their belief that it has not been implemented in a memory model, although it actually has been implemented in ACT-R (L. J. Schooler & R. Hertwig, 2005). On the positive side, M. R. Dougherty et al. discovered a new mechanism for a less-is-more effect. The authors of the present article specify minimal criteria for psychological plausibility, describe some genuine challenges in the study of heuristics, and conclude that fast and frugal heuristics are psychologically plausible: They use limited search and are tractable and robust.     

The priority heuristic: making choices without trade-offs

Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, the authors generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (a) the Allais paradox, (b) risk aversion for gains if probabilities are high, (c) risk seeking for gains if probabilities are low (e.g., lottery tickets), (d) risk aversion for losses if probabilities are low (e.g., buying insurance), (e) risk seeking for losses if probabilities are high, (f) the certainty effect, (g) the possibility effect, and (h) intransitivities. The authors test how accurately the heuristic predicts people's choices, compared with previously proposed heuristics and 3 modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory.     

Integrating Fast and Frugal Heuristics with a Model of Memory‐based Cue Generation

Although the fast and frugal heuristics have been studied extensively, relatively little attention has been paid to how cues are generated to be used within the heuristics. The goal of this paper is to propose and test a memory‐based model of how cues are generated and used in cue‐based inferences. The current study advances theory by integrating the fast and frugal heuristics with HyGene, a memory‐based model of how decision makers generate and evaluate hypotheses. Using archival data in which memory retrieval variables were not directly manipulated, we demonstrate that participants' cue selection behavior is consistent with memory‐based retrieval. Further, by directly manipulating memory retrieval within a cue‐based stock‐forecasting task, we demonstrate that memory processes underlie cue use. Participants' cue use varied depending on the relationship between cue validity and the frequency with which the cues were seen during learning. The HyGene model provided the best account of the empirical data, providing further evidence for the critical role of memory in judgment and decision making. Copyright © 2018 John Wiley & Sons, Ltd.     

How (far) can rationality be naturalized?

The paper shows why and how an empirical study of fast-and-frugal heuristics can provide norms of good reasoning, and thus how (and how far) rationality can be naturalized. We explain the heuristics that humans often rely on in solving problems, for example, choosing investment strategies or apartments, placing bets in sports, or making library searches. We then show that heuristics can lead to judgments that are as accurate as or even more accurate than strategies that use more information and computation, including optimization methods. A standard way to defend the use of heuristics is by reference to accuracy-effort trade-offs. We take a different route, emphasizing ecological rationality (the relationship between cognitive heuristics and environment), and argue that in uncertain environments, more information and computation are not always better (the ??less-can-be-more?? doctrine). The resulting naturalism about rationality is thus normative because it not only describes what heuristics people use, but also in which specific environments one should rely on a heuristic in order to make better inferences. While we desist from claiming that the scope of ecological rationality is unlimited, we think it is of wide practical use.