
Contents
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THE TASK THE TASK
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THEORY THEORY
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Limited Knowledge Limited Knowledge
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The Take-the-Best Algorithm The Take-the-Best Algorithm
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Step 1: Recognition Principle Step 1: Recognition Principle
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Step 2: Search for Cue Values Step 2: Search for Cue Values
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Step 3: Discrimination Rule Step 3: Discrimination Rule
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Step 4: Cue-Substitution Principle Step 4: Cue-Substitution Principle
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Step 5: Maximizing Rule for Choice Step 5: Maximizing Rule for Choice
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Empirical Evidence Empirical Evidence
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THE ENVIRONMENT THE ENVIRONMENT
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THE COMPETITION THE COMPETITION
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Simulating Limited Knowledge Simulating Limited Knowledge
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Testing the Take-the-Best Algorithm Testing the Take-the-Best Algorithm
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Integration Algorithms Integration Algorithms
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Contestant 1: Tallying Contestant 1: Tallying
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Contestant 2: Weighted Tallying Contestant 2: Weighted Tallying
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Contestant 3: Unit-Weight Linear Model Contestant 3: Unit-Weight Linear Model
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Contestant 4: Weighted Linear Model Contestant 4: Weighted Linear Model
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Contestant 5: Multiple Regression Contestant 5: Multiple Regression
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Results Results
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CAN SATISFICING ALGORITHMS GET BY WITH EVEN LESS TIME AND KNOWLEDGE? CAN SATISFICING ALGORITHMS GET BY WITH EVEN LESS TIME AND KNOWLEDGE?
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The Take-the-Last Algorithm The Take-the-Last Algorithm
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Step 2': Search for the Cue Values of the Most Recent Cue Step 2': Search for the Cue Values of the Most Recent Cue
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The Minimalist Algorithm The Minimalist Algorithm
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Step 2: Random Search Step 2: Random Search
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Results Results
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DISCUSSION DISCUSSION
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Cognitive Algorithms That Satisfice Cognitive Algorithms That Satisfice
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One-Reason Decision Making One-Reason Decision Making
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Intransitivity Intransitivity
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Cue Redundancy and Performance Cue Redundancy and Performance
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A New Perspective on the Lens Model A New Perspective on the Lens Model
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Can Reasoning Be Rational and Psychological? Can Reasoning Be Rational and Psychological?
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ACKNOWLEDGMENTS ACKNOWLEDGMENTS
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NOTES NOTES
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APPENDIX APPENDIX
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The Environment The Environment
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23 On the Psychology of the Recognition Heuristic: Retrieval Primacy as a Key Determinant of Its Use
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2 Reasoning the Fast and Frugal Way: Models of Bounded Rationality
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Published:April 2011
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Abstract
Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following Herbert Simon's notion of satisficing, this chapter proposes a family of algorithms based on a simple psychological mechanism: one-reason decision making. These fast-and-frugal algorithms violate fundamental tenets of classical rationality: It neither looks up nor integrates all information. By computer simulation, a competition was held between the satisficing “take-the-best” algorithm and various “rational” inference procedures (e.g., multiple regression). The take-the-best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference.
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