Individual differences in fast-and-frugal decision making: Neuroticism and the recognition heuristic

The fast-and-frugal recognition heuristic (RH) claims that people base inferences on recognition only, thus ignoring further knowledge they possess. This claim has been repeatedly challenged, while recent evidence suggests that there are substantial individual differences in adhering to the RH. However, no personality or ability factors driving (non-)use of the RH have, as yet, been identified. In the present study, neuroticism was hypothesized to be a determinant of using the RH: participants high in neuroticism were expected to avoid making use of their knowledge beyond recognition, thus avoiding a diagnostic test of their abilities. The results corroborate this hypothesis: neuroticism predicted participants’ adherence to the RH while the other Big 5 factors and intelligence yielded no additional explanatory power. Moreover, the effect of neuroticism was not mediated by the accessibility of knowledge thus lending preliminary support for the notion that this effect may, in fact, be genuinely motivational in nature.     

Environments That Make Us Smart: Ecological Rationality

ABSTRACT— Traditional views of rationality posit general-purpose decision mechanisms based on logic or optimization. The study of ecological rationality focuses on uncovering the "adaptive toolbox" of domain-specific simple heuristics that real, computationally bounded minds employ, and explaining how these heuristics produce accurate decisions by exploiting the structures of information in the environments in which they are applied. Knowing when and how people use particular heuristics can facilitate the shaping of environments to engender better decisions.     

A variable-selection heuristic for K-means clustering

One of the most vexing problems in cluster analysis is the selection and/or weighting of variables in order to include those that truly define cluster structure, while eliminating those that might mask such structure. This paper presents a variable-selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. The heuristic was subjected to Monte Carlo testing across more than 2200 datasets with known cluster structure. The results indicate the heuristic is extremely effective at eliminating masking variables. A cluster analysis of real-world financial services data revealed that using the variable-selection heuristic prior to the K-means algorithm resulted in greater cluster stability.     

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.     

对相容和不相容析取关系下析取句与条件句之间推理的比较

研究析取句和条件句之间的推理能检验推理心理学中的主要理论解释。一个实验考察了析取句和条件句中两个基本成分之间的关系(相容析取与不相容析取)和推理方向(由析取句推条件句与由条件句推析取句)对析取句与其等值的条件句之间推理的影响。结果发现,推理方向的影响取决于条件句和析取句中基本成分间的关系,在不相容析取关系下的推理成绩好于在相容析取关系下的推理成绩。现有的推理理论不能解释被试的整体反应模式,作者提出的特殊知识启发式与一般的句法意义对比启发式的竞争能统一解释被试的主导反应模式。     

Achieving what cannot be done: coping with the time constants in a dynamic decision task by doing something else

This study examines how people handle the time constants in dynamic decision tasks, using a microworld called NEWFIRE which simulates forest fire fighting. The results showed that the participants did not adapt to the time constants, as shown by the fact that they did not discriminate between fires requiring different number of fire fighting units when varying the number of fire fighting units was a means of compensating for the time constants. If they were allowed to move units before the fire started their performance improved, suggesting that they could compensate for their problems with the time constants by restructuring the task in such a way that they did not need to consider them. It is suggested that such restructuring may well be how people handle dynamic tasks also in other circumstances, and that more effort should be put into studying what people actually do in dynamic tasks, rather than into only assessing whether or not they perform optimally.     

A Comparison of Heuristic Procedures for Minimum Within-Cluster Sums of Squares Partitioning

Perhaps the most common criterion for partitioning a data set is the minimization of the within-cluster sums of squared deviation from cluster centroids. Although optimal solution procedures for within-cluster sums of squares (WCSS) partitioning are computationally feasible for small data sets, heuristic procedures are required for most practical applications in the behavioral sciences. We compared the performances of nine prominent heuristic procedures for WCSS partitioning across 324 simulated data sets representative of a broad spectrum of test conditions. Performance comparisons focused on both percentage deviation from the “best-found” WCSS values, as well as recovery of true cluster structure. A real-coded genetic algorithm and variable neighborhood search heuristic were the most effective methods; however, a straightforward two-stage heuristic algorithm, HK-means, also yielded exceptional performance. A follow-up experiment using 13 empirical data sets from the clustering literature generally supported the results of the experiment using simulated data. Our findings have important implications for behavioral science researchers, whose theoretical conclusions could be adversely affected by poor algorithmic performances.     

Probability Biases in Genetic Problem Solving: A Comparison of Undergraduates, Genetic Counseling Graduate Students, and Genetic Counselors

Heuristics are mental shortcuts that aid people in everyday problem-solving and decision-making. Although numerous studies have demonstrated their use in contexts ranging from consumers’ shopping decisions to experts’ estimations of experimental validity, virtually no published research has addressed heuristics use in problems involving genetic conditions and associated risk probabilities. The present research consists of two studies. In the first study, 220 undergraduates attempted to solve four genetic problems—two common heuristic problems modified to focus on genetic likelihood, and two created to study heuristics and probability rule application. Results revealed that the vast majority of undergraduates used heuristics and also demonstrated a complete misuse of probability rules. In the second study, 156 practicing genetic counselors and 89 genetic counseling students solved slightly modified versions of the genetic problems used in Study 1. Results indicated that a large percentage of both genetic counselors and students used heuristics, but the counselors demonstrated superior problem-solving performance compared to both the genetic counseling students and the undergraduates from Study 1. Research, training, and practice recommendations are presented.     

Compound cue processing within the fast and frugal heuristics approach in nonlinearly separable environments

Three experiments investigated whether participants used Take The Best (TTB) Configural, a fast and frugal heuristic that processes configurations of cues when making inferences concerning which of two alternatives has a higher criterion value. Participants were presented with a compound cue that was nonlinearly separable from its elements. The compound was highly valid in Experiments 1 and 2, but invalid in Experiment 3. Participants’ causal mental models were manipulated via instructions: participants were either told that cues acted through the same causal mechanism (configural causal model), through different causal mechanisms (elemental causal model), or the causal mechanisms were not specified (neutral causal model). A high percentage of participants used TTB-Configural when they had a configural causal model and a highly valid compound existed, suggesting that causal knowledge can be incorporated in otherwise very basic cognitive mechanisms to allow fine-grained adaptation to complex task structures.