Heuristics and Biases: The Psychology of Intuitive Judgment

2004 ◽  
Vol 29 (4) ◽  
pp. 695 ◽  
Author(s):  
William P. Bottom ◽  
Thomas Gilovich ◽  
Dale Griffin ◽  
Daniel Kahneman
Keyword(s):  
Heuristics And Biases ◽  
Intuitive Judgment

HEURISTICS AND BIASES: IMPLICATIONS AND SOLUTIONS FOR MARKETING RESEARCH AND PRACTICE

2018 ◽  
Vol 2018 ◽  
pp. 480-480
Author(s):  
Cuong Pham ◽  
◽  
Bo Pang ◽  
Julia Carins ◽  
Sharyn Rundle-thiele
Keyword(s):  
Marketing Research ◽  
Heuristics And Biases ◽  
Research And Practice

scholarly journals Cognition, heuristics, and biases behind environment-related behaviours

2018 ◽  
Vol 2 (1) ◽  
pp. e11 ◽  
Author(s):  
Silvia Riva ◽  
Ezekiel Chinyio ◽  
Paul Hampton
Keyword(s):  
Heuristics And Biases

scholarly journals Strategy selection as rational metareasoning

2016 ◽  
Author(s):  
Falk Lieder ◽  
Tom Griffiths
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Cost Benefit ◽  
Human Reasoning ◽  
Strategy Selection ◽  
Heuristics And Biases ◽  
Rational Model ◽  
The Mind ◽  
Over Time ◽  
Human Rationality

Many contemporary accounts of human reasoning assume that the mind is equipped with multiple heuristics that could be deployed to perform a given task. This raises the question how the mind determines when to use which heuristic. To answer this question, we developed a rational model of strategy selection, based on the theory of rational metareasoning developed in the artificial intelligence literature. According to our model people learn to efficiently choose the strategy with the best cost-benefit tradeoff by learning a predictive model of each strategy’s performance. We found that our model can provide a unifying explanation for classic findings from domains ranging from decision-making to problem-solving and arithmetic by capturing the variability of people’s strategy choices, their dependence on task and context, and their development over time. Systematic model comparisons supported our theory, and four new experiments confirmed its distinctive predictions. Our findings suggest that people gradually learn to make increasingly more rational use of fallible heuristics. This perspective reconciles the two poles of the debate about human rationality by integrating heuristics and biases with learning and rationality.

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