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The computational cost of active information sampling before decision-making under uncertainty
Pierre Petitet1, Bahaaeddin Attaallah2, Sanjay G Manohar3,2
1Department of Experimental Psychology, University of Oxford, Oxford, UK. pierre.petitet@gmail.com.
Nature Human Behaviour
|May 28, 2021
Summary
Humans actively seek information to reduce decision uncertainty. New research shows cognitive effort, not just task costs, influences information gathering speed and efficiency.
Area of Science:
- Cognitive psychology
- Decision science
- Computational neuroscience
Background:
- Existing decision theories focus on information cost-benefit analysis.
- These models overlook the cognitive effort involved in information acquisition.
Purpose of the Study:
- To investigate the role of cognitive effort in information seeking during decision-making.
- To explore the trade-off between sampling speed and information quality.
- To model how cognitive effort impacts information gathering behavior.
Main Methods:
- Development of an active sampling computational model.
- Experimental manipulation of time pressure during information seeking.
- Analysis of sampling speed, efficiency, and self-reported fatigue.
Main Results:
- A speed-efficiency trade-off exists: more informative samples require more time.
- Under time pressure, individuals can sample information faster and more efficiently.
- Computational models incorporating cognitive effort cost better predict human behavior and fatigue.
Conclusions:
- Decision-making information seeking is influenced by both external task costs and internal cognitive effort costs.
- Cognitive effort is a quantifiable factor that shapes how people acquire knowledge.
- Understanding cognitive effort is crucial for accurate models of human decision-making.
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