The Role of Mental Simulation in Judgments of Likelihood

Dougherty, Michael R.; Gettys, Charles F.; Thomas, Rick P.

doi:10.1006/obhd.1997.2700

Cited by 69 publications

(50 citation statements)

References 25 publications

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“…Failures in this process characterize profound examples of mental illness-like entertaining the hypothesis that the kitchen faucet is communicating with you when the dripping is perfectly consistent with its just being leaky. At the same time, the HyGene model predicts that the most likely hypotheses will be generated first, another prediction consistent with the literature (Dougherty et al, 1997;Dougherty & Hunter, 2003a;Sprenger & Dougherty, 2012;Weber et al, 1993). The HyGene model assumes this result because hypotheses that have occurred more often in a person's experience are more prevalent in long-term memory, which results in greater activations of hypotheses with higher a priori likelihood.…”

Section: Memory Processes Constrain Hypothesis Generationsupporting

confidence: 78%

Memory Constraints on Hypothesis Generation and Decision Making

Thomas

Dougherty

Buttaccio

2014

Curr Dir Psychol Sci

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Hypothesis generation is the process people use to generate explanations for patterns of data, which is an act vital to everyday problem solving. It is the basis for decision making in many professions, such as medicine, intelligence and reconnaissance analysis, auditing, and fault detection in nuclear power plants. Even laypeople's impressions of acquaintances' personalities based on behavioral patterns can be considered a case of hypothesis generation. This article provides an overview of research elucidating the cognitive processes that underlie hypothesis generation and decision making.

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Section: Memory Processes Constrain Hypothesis Generationsupporting

confidence: 78%

Memory Constraints on Hypothesis Generation and Decision Making

Thomas

Dougherty

Buttaccio

2014

Curr Dir Psychol Sci

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“…However, it is also useful to consider that they are two extremes in terms of how information about alternatives contributes to sampling decisions. In many domains, the generation and/or use of alternatives has been linked to how people reason and the quality of their decisions (Dougherty, Gettys, & Thomas, 1997;Evans, 2007;Newstead et al, 2002;Sprenger et al, 2011;Thomas, Dougherty, Sprenger, & Harbison, 2008). The consideration of alternatives has often been proposed as a critical factor mediating whether people engage in confirmatory or normative sampling (Sanbonmatsu, Posavac, Kardes, & Mantel, 1998), but these behaviors have often been treated as a dichotomy rather than as endpoints on a continuum.…”

Section: Discussionmentioning

confidence: 99%

Self‐Directed Learning Favors Local, Rather Than Global, Uncertainty

2015

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Collecting (or "sampling") information that one expects to be useful is a powerful way to facilitate learning. However, relatively little is known about how people decide which information is worth sampling over the course of learning. We describe several alternative models of how people might decide to collect a piece of information inspired by "active learning" research in machine learning. We additionally provide a theoretical analysis demonstrating the situations under which these models are empirically distinguishable, and we report a novel empirical study that exploits these insights. Our model-based analysis of participants' information gathering decisions reveals that people prefer to select items which resolve uncertainty between two possibilities at a time rather than items that have high uncertainty across all relevant possibilities simultaneously. Rather than adhering to strictly normative or confirmatory conceptions of information search, people appear to prefer a "local" sampling strategy, which may reflect cognitive constraints on the process of information gathering.

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“…Elstein et al (1978) observed that expert physicians generated only about four alternative diagnoses prior to settling upon one. Finally, Dougherty, Gettys, and Thomas (1997) found that participants generated at most one or two alternative hypotheses when judging the probability of a particular causal scenario.…”

Section: Hypothesis Generationmentioning

confidence: 98%

Diagnostic hypothesis generation and human judgment.

Thomas

Dougherty

Sprenger

et al. 2008

Psychological Review

187

205

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Diagnostic hypothesis-generation processes are ubiquitous in human reasoning. For example, clinicians generate disease hypotheses to explain symptoms and help guide treatment, auditors generate hypotheses for identifying sources of accounting errors, and laypeople generate hypotheses to explain patterns of information (i.e., data) in the environment. The authors introduce a general model of human judgment aimed at describing how people generate hypotheses from memory and how these hypotheses serve as the basis of probability judgment and hypothesis testing. In 3 simulation studies, the authors illustrate the properties of the model, as well as its applicability to explaining several common findings in judgment and decision making, including how errors and biases in hypothesis generation can cascade into errors and biases in judgment.

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The Role of Mental Simulation in Judgments of Likelihood

Cited by 69 publications

References 25 publications

Memory Constraints on Hypothesis Generation and Decision Making

Memory Constraints on Hypothesis Generation and Decision Making

Self‐Directed Learning Favors Local, Rather Than Global, Uncertainty

Diagnostic hypothesis generation and human judgment.

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