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Multi-attribute utility models as cognitive search engines. Judgment and Decision Making
, 2014
"... Abstract In optimal stopping problems, decision makers are assumed to search randomly to learn the utility of alternatives; in contrast, in one-shot multi-attribute utility optimization, decision makers are assumed to have perfect knowledge of utilities. We point out that these two contexts represe ..."
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Abstract In optimal stopping problems, decision makers are assumed to search randomly to learn the utility of alternatives; in contrast, in one-shot multi-attribute utility optimization, decision makers are assumed to have perfect knowledge of utilities. We point out that these two contexts represent the boundaries of a continuum, of which the middle remains uncharted: How should people search intelligently when they possess imperfect information about the alternatives? We assume that decision makers first estimate the utility of each available alternative and then search the alternatives in order of their estimated utility until expected benefits are outweighed by search costs. We considered three well-known models for estimating utility: (i) a linear multi-attribute model, (ii) equal weighting of attributes, and (iii) a single-attribute heuristic. We used 12 real-world decision problems, ranging from consumer choice to industrial experimentation, to measure the performance of the three models. The full model (i) performed best on average but its simplifications (ii and iii) also had regions of superior performance. We explain the results by analyzing the impact of the models' utility order and estimation error.
The beauty of simple models: Themes in recognition heuristic research
"... The advantage of models that do not use flexible parameters is that one can precisely show to what degree they predict behavior, and in what situations. In three issues of this journal, the recognition heuristic has been examined carefully from many points of view. We comment here on four themes, th ..."
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The advantage of models that do not use flexible parameters is that one can precisely show to what degree they predict behavior, and in what situations. In three issues of this journal, the recognition heuristic has been examined carefully from many points of view. We comment here on four themes, the use of optimization models to understand the rationality of heuristics, the generalization of the recognition input beyond a binary judgment, new conditions for less-is-more effects, and the importance of specifying boundary conditions for cognitive heuristics.
35th Annual Meeting of the Cognitive Science Society (CogSci 2013), Tutorial 7: Making Robust Classification Decisions: Constructing and Evaluating Fast and Frugal Trees (FFTs)
"... Fast and Frugal Trees (FFTs) are a quintessential family of simple heuristics that allow effective and efficient binary classification decisions and often perform remarkably well when compared to more complex methods. This half-‐‑day tutorial will familiarize participants with examples of FFTs and e ..."
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Fast and Frugal Trees (FFTs) are a quintessential family of simple heuristics that allow effective and efficient binary classification decisions and often perform remarkably well when compared to more complex methods. This half-‐‑day tutorial will familiarize participants with examples of FFTs and elucidate the theoretical link between FFTs and signal detection theory (SDT). A range of presentations, practical exercises and interactive tools will enable participants to construct and evaluate FFTs for different data sets.
Draft in APA-style; please do not cite this version. Homo Heuristicus in the Financial World: From Risk Management to Managing Uncertainty
, 2013
"... What—if anything—can psychology and decision science contribute to risk management in financial institutions? The turmoils of recent economic crises undermine the assumptions of classical economic models and threaten to dethrone Homo oeconomicus, who aims to make decisions by weighing and integratin ..."
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What—if anything—can psychology and decision science contribute to risk management in financial institutions? The turmoils of recent economic crises undermine the assumptions of classical economic models and threaten to dethrone Homo oeconomicus, who aims to make decisions by weighing and integrating all available information. But rather than aiming to replace the rational actor model with irrational, biased, and fundamentally flawed agents, we advocate the alternative notion of Homo heuristicus, who uses simple, but ecologically rational strategies to make sound and robust decisions. Based on the conceptual distinction between risky and uncertain environments we present theoretical and empirical evidence that boundedly rational agents prefer simple heuristics over more flexible models. We provide examples of successful heuristics, explain when and why heuristics work well, and illustrate these insights with a fast and frugal decision tree that helps to identify fragile banks. We conclude that all members of the financial community will benefit from simpler and more transparent products and regulations.
What a____ _ Thing to Do! Formally Characterizing Actions by Their Expected Effects Dustin Wood
"... A number of personality frameworks assume traits describe central tendencies of action—for instance, calling someone assertive indicates they have a tendency to perform assertive actions. But what makes it appropriate to characterize an action by terms like assertive, kind, or honest? We propose tha ..."
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A number of personality frameworks assume traits describe central tendencies of action—for instance, calling someone assertive indicates they have a tendency to perform assertive actions. But what makes it appropriate to characterize an action by terms like assertive, kind, or honest? We propose that actions are characterized by such terms in large part by having expected effects on the environment which match particular conceptual templates. In the present studies, we attempt to better identify the expected effect dimensions perceivers seem to utilize to make action characterizations related to the Big Five and HEXACO personality dimensions. To do so, a set of 150 situation-action scenarios were generated from actions suggestive of conscientiousness-related characteristics (Study 1), and of characteristics in other HEXACO domains (Study 2). Participants then characterized each action on a range of bipolar dimensions (e.g., assertive vs. submissive). A separate group of raters coded the expected effects of performing these actions on 21 different outcomes (e.g., effort expenditure; achievement of career goals). Action characterizations were highly predicted by expected effect dimensions in ways that matched provisional hypotheses and were consistent across studies. Furthermore, actions characterizations tended to be highly diagnostic of self-reported individual differences in the same characteristics. We discuss implications for a range of phenomena, such as understanding the relations between behaviors and traits, integrating trait models and decision-making models, and understanding the effect of situational features on personality traits.
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, 2012
"... Cognitive processes in decisions under risk are not the same as in decisions under uncertainty ..."
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Cognitive processes in decisions under risk are not the same as in decisions under uncertainty
