Header logo is

Strategy selection as rational metareasoning

2017

Article

re


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 of 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 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 4 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 2 poles of the debate about human rationality by integrating heuristics and biases with learning and rationality. (APA PsycInfo Database Record (c) 2017 APA, all rights reserved)

Author(s): Falk Lieder and Thomas L. Griffiths
Journal: Psychological Review
Volume: 124
Pages: 762--794
Year: 2017
Month: November
Publisher: American Psychological Association

Department(s): Rationality Enhancement
Research Project(s): Metacognitive Learning
Bibtex Type: Article (article)
Paper Type: Journal

DOI: https://doi.org/10.1037/rev0000075
Language: English
State: Published

BibTex

@article{lieder2017strategy,
  title = {Strategy selection as rational metareasoning},
  author = {Lieder, Falk and Griffiths, Thomas L.},
  journal = {Psychological Review},
  volume = {124},
  pages = {762--794},
  publisher = {American Psychological Association},
  month = nov,
  year = {2017},
  month_numeric = {11}
}