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Discovering Rational Heuristics for Risky Choice

2018

Conference Paper

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How should we think and decide to make the best possible use of our precious time and limited cognitive resources? And how do people’s cognitive strategies compare to this ideal? We study these questions in the domain of multi-alternative risky choice using the methodology of resource-rational analysis. To answer the first question, we leverage a new meta-level reinforcement learning algorithm to derive optimal heuristics for four different risky choice environments. We find that our method rediscovers two fast-and-frugal heuristics that people are known to use, namely Take-The-Best and choosing randomly, as resource-rational strategies for specific environments. Our method also discovered a novel heuristic that combines elements of Take-The-Best and Satisficing. To answer the second question, we use the Mouselab paradigm to measure how people’s decision strategies compare to the predictions of our resource-rational analysis. We found that our resource-rational analysis correctly predicted which strategies people use and under which conditions they use them. While people generally tend to make rational use of their limited resources overall, their strategy choices do not always fully exploit the structure of each decision problem. Overall, people’s decision operations were about 88% as resource-rational as they could possibly be. A formal model comparison confirmed that our resource-rational model explained people’s decision strategies significantly better than the Directed Cognition model of Gabaix et al. (2006). Our study is a proof-of-concept that optimal cognitive strategies can be automatically derived from the principle of resource-rationality. Our results suggest that resource-rational analysis is a promising approach for uncovering people’s cognitive strategies and revisiting the debate about human rationality with a more realistic normative standard.

Author(s): Sayan Gul and Paul M. Krueger and Frederick Callaway and Thomas L. Griffiths and Falk Lieder
Book Title: The 14th biannual conference of the German Society for Cognitive Science, GK
Year: 2018
Month: September

Department(s): Rationality Enhancement
Research Project(s): Metacognitive Learning
Bibtex Type: Conference Paper (conference)
Paper Type: Abstract

Event Name: The 14th biannual conference of the German Society for Cognitive Science, GK

State: Published
URL: http://cocosci.princeton.edu/falk/KogWis_Discovering_Heuristics.pdf

BibTex

@conference{Gul2018Discovering,
  title = {Discovering Rational Heuristics for Risky Choice},
  author = {Gul, Sayan and Krueger, Paul M. and Callaway, Frederick and Griffiths, Thomas L. and Lieder, Falk},
  booktitle = {The 14th biannual conference of the German Society for Cognitive Science, GK},
  month = sep,
  year = {2018},
  url = {http://cocosci.princeton.edu/falk/KogWis_Discovering_Heuristics.pdf},
  month_numeric = {9}
}