Showing papers on "Fuzzy-trace theory published in 2014"
TL;DR: The results show that, although framing biases are irrational, they are the ironical output of cognitively advanced mechanisms of meaning making, and the growth of experience-based intuition predicts this developmental reversal.
Abstract: Intelligence agents make risky decisions routinely, with serious consequences for national security. Although common sense and most theories imply that experienced intelligence professionals should be less prone to irrational inconsistencies than college students, we show the opposite. Moreover, the growth of experience-based intuition predicts this developmental reversal. We presented intelligence agents, college students, and postcollege adults with 30 risky-choice problems in gain and loss frames and then compared the three groups' decisions. The agents not only exhibited larger framing biases than the students, but also were more confident in their decisions. The postcollege adults (who were selected to be similar to the students) occupied an interesting middle ground, being generally as biased as the students (sometimes more biased) but less biased than the agents. An experimental manipulation testing an explanation for these effects, derived from fuzzy-trace theory, made the students look as biased as the agents. These results show that, although framing biases are irrational (because equivalent outcomes are treated differently), they are the ironical output of cognitively advanced mechanisms of meaning making.
113 citations
TL;DR: The authors found that those with higher levels of Need for Cognition are more likely to elaborate and infer information from advertising that causes them to create "smart" false memories, which are explained by fuzzy trace theory.
Abstract: False memories are generally viewed as “dumb,” in the sense of being caused by deficient processing, but recent psychological research has shown that elaboration and inferences can result in “smart” false memories. These “smart” false memories are explained by fuzzy-trace theory (FTT), which assumes that they derive from comprehension of the meaning of experience. FTT predicts that “smart” false memories should be positively correlated with measured levels of Need for Cognition (NFC). In three experiments we find those higher in NFC are more likely to elaborate and infer information from advertising that causes them to create “smart” false memories.
24 citations
TL;DR: In this article, the authors focus on information processing, and specifically, the use of gist and verbatim representations to guide memory, reasoning, and concept formation, and demonstrate the utility of Fuzzy Trace Theory to the field of ASD research.
22 citations
11 Jul 2014
TL;DR: In this article, the authors studied decision processes through Behavioral and Neuroscience Analyses of Framing Effects, I.P. Levin, T.C. McElroy, G.M.Reyna, P.G. Brust-Renck.
Abstract: Part 1. Historical Foundations. Decision Making by Experts: Influence of Five Key Psychologists, J. Shanteau, W. Edwards. Part 2. Cognitive Consistency and Inconsistency. Cognitive Consistency: Cognitive and Motivational Perspectives, A.S. Chaxel, J. Edward Russo. Fuzzy Trace Theory Explains Paradoxical Dissociations in Affective Forecasting, E.A. Wilhelms, R.A. Setton, R.K. Helm, V.F. Reyna. Part 3. Heuristics and Biases. Intuition, Inhibition, Interference, and Individual Differences in Fuzzy Trace Theory, J.C. Corbin, J.M. Liberali, V.F.Reyna, P.G. Brust-Renck. The Predecisional Distortion of Information, J.E. Russo. The Precision Effect: How Numerical Precision Influences Everyday Judgments, M.Thomas, J. Park. Part 4. Neuroeconomics and Neurobiology. Studying Decision Processes Through Behavioral and Neuroscience Analyses of Framing Effects, I.P. Levin, T. McElroy, G.J. Gaeth, W. Hedgcock, N.L. Denburg, D. Tranel. "Hot" Cognition and Dual Systems: Introduction, Criticisms, and Ways Forward. T.E. Gladwin, B. Figner. Neuroeconomics and Dual Information Processes Underlying Charitable Giving, S. Dickert, D.Vastfjall, P. Slovic. Part 5. Developmental and Individual Differences. Choice from Childhood to Adulthood: Changes in Decision Strategies, Affect, and Control. A.C.K. van Duijvenvoorde, B.R.J. Jansen, H.M. Huizenga. Individual Differences in Decision-making Competence Across the Lifespan, W. Bruine de Bruin, A.M. Parker, B. Fischhoff. Part 6. Improving Decisions. Improving Judgments and Decisions by Experiencing Simulated Outcomes, R.M. Hogarth, E. Soyer. Predictors of Risky Decisions: Improving Judgment and Decision Making Based on Evidence from Phishing Attacks, J. Downs, A. Acquisti, D. Barbagallo
17 citations
01 Jan 2014
TL;DR: Many examples exist in real-world settings that highlight the importance of examining the veracity of recalled memories as discussed by the authors, such as the one presented in this paper. But these examples are limited to real-life scenarios.
Abstract: Many examples exist in real-world settings that highlight the importance of examining the veracity of recalled memories.
11 citations
01 Dec 2014
TL;DR: The basic tenets of fuzzy trace theory are presented, a comprehensive theory of memory, judgment, and decision making that is grounded in research on how information is stored as knowledge, mentally represented, retrieved from storage, and processed.
Abstract: We present the basic tenets of fuzzy trace theory, a comprehensive theory of memory, judgment, and decision making that is grounded in research on how information is stored as knowledge, mentally represented, retrieved from storage, and processed. In doing so, we highlight how it is distinguished from traditional models of decision making in that gist reasoning plays a central role. The theory also distinguishes advanced intuition from primitive impulsivity. It predicts that different sorts of errors occur with respect to each component of judgment and decision making: background knowledge, representation, retrieval, and processing. Classic errors in the judgment and decision making literature, such as risky-choice framing and the conjunction fallacy, are accounted for by fuzzy trace theory and new results generated by the theory contradict traditional approaches. We also describe how developmental changes in brain and behavior offer crucial insight into adult cognitive processing. Research investigating brain and behavior in developing and special populations supports fuzzy trace theory's predictions about reliance on gist processing.
8 citations
TL;DR: Two experiments investigated the cognitive skills that underlie children's susceptibility to semantic and phonological false memories in the Deese/Roediger-McDermott procedure and found that auditory short-term memory was a negative predictor of false recall in Experiment 1, but not in Experiment 2.
8 citations
01 Jan 2014
8 citations
TL;DR: This article investigated whether knowledge of, and familiarity with types of environments influenced the quantity, accuracy, and errors recalled by children (4- to 6- year-olds) and adults.
7 citations
TL;DR: This family of models is developed and the requisite machinery for fit evaluation and significance testing is presented and results are reviewed from selected experiments in which the recall models were used to understand dual memory processes.
7 citations
Journal Article•
TL;DR: A novel formalization of Fuzzy Trace Theory (FTT), a leading theory of decision- making under risk, which assumes that decision-makers use a qualitative “gist” representation of a stimulus, in parallel with a precise verbatim representation.
01 Apr 2014
TL;DR: A computational model of Fuzzy Trace Theory is presented, which is able to successfully predict 14 experimental effects using a small number of assumptions, and may ultimately form the basis for an agent-based model, whose rule sets incorporate cultural and other psychosocial factors.
Abstract: Most leading computational theories of decision-making under risk do not have mechanisms to account for the incorporation of cultural factors. Therefore, they are of limited utility to scholars and practitioners who wish to model, and predict, how culture influences decision outcomes. Fuzzy Trace Theory (FTT) posits that people encode risk information at multiple levels of representation – namely, gist, which captures the culturally contingent meaning, or interpretation, of a stimulus, and verbatim, which is a detailed symbolic representation of the stimulus. Decision-makers prefer to rely on gist representations, although conflicts between gist and verbatim can attenuate this reliance. In this paper, we present a computational model of Fuzzy Trace Theory, which is able to successfully predict 14 experimental effects using a small number of assumptions. This technique may ultimately form the basis for an agent-based model, whose rule sets incorporate cultural and other psychosocial factors.
23 Jan 2014
TL;DR: How a brain-based neural network model of other decision data that combines fuzzy trace theory with adaptive resonance theory can be extended to these framing data is discussed.
Abstract: In a decision study called the Asian Disease Problem, Tversky and Kahneman [1] found that framing risky health choices in terms of gains or losses of lives leads to radically different choices: risk seeking for losses and risk avoidance for gains. The difference between the two choices is called the framing effect. The authors explained framing effects via psychophysics of the numbers of lives saved or lost. Yet Reyna and Brainerd [2] showed that the strength of the framing effect depended not on the numbers but on whether one of options explicitly contained the possibility of no lives lost or saved. They fit their explanation into fuzzy trace theory whereby decisions are based not on details of the options given but on the gist (underlying meaning) of the options. We discuss how a brain-based neural network model of other decision data [3] that combines fuzzy trace theory with adaptive resonance theory can be extended to these framing data. Simulations are in progress.
01 Jan 2014
TL;DR: In this paper, a computational model of Fuzzy Trace Theory is presented, which is able to successfully predict 14 experimental effects using a small number of assumptions, which may ultimately form the basis for an agent-based model, whose rule sets incorporate cultural and other psychosocial factors.
Abstract: Most leading computational theories of decision-making under risk do not have mechanisms to account for the incorporation of cultural factors. Therefore, they are of limited utility to scholars and practitioners who wish to model, and predict, how culture influences decision outcomes. Fuzzy Trace Theory (FTT) posits that people encode risk information at multiple levels of representation - namely, gist, which captures the culturally contingent meaning, or interpretation, of a stimulus, and verbatim, which is a detailed symbolic re- presentation of the stimulus. Decision-makers prefer to rely on gist representa- tions, although conflicts between gist and verbatim can attenuate this reliance. In this paper, we present a computational model of Fuzzy Trace Theory, which is able to successfully predict 14 experimental effects using a small number of assumptions. This technique may ultimately form the basis for an agent-based model, whose rule sets incorporate cultural and other psychosocial factors.