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Normative Principles for Decision-Making in Natural Environments.

Christopher Summerfield1, Paula Parpart1

  • 1Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom;

Annual Review of Psychology
|September 23, 2021
PubMed
Summary
This summary is machine-generated.

Lifelong learning and context shape our decisions by influencing neural encoding and retrieval. A unified framework using efficient coding and Bayesian inference explains diverse human decision biases.

Keywords:
decision-makingecological approachefficient codingoptimalitypsychophysicsvaluation

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Behavioral Economics

Background:

  • Human decisions are influenced by past experiences, affecting information processing in perception and valuation.
  • Separate research fields explore how lifelong learning and context impact decisions in sensory, propositional, and economic domains.

Purpose of the Study:

  • To integrate diverse research on decision-making by proposing common principles of adaptive rationality.
  • To present a unified computational framework explaining a wide range of human decision biases.

Main Methods:

  • Review and synthesis of existing literature on learning, perception, and economic choice.
  • Development of a computational framework based on normative principles of efficient coding and Bayesian inference.

Main Results:

  • Demonstration that a single framework can explain numerous decision biases, including sensory illusions, anchoring, and framing effects.
  • Identification of common principles underlying adaptive rationality across different decision-making contexts.

Conclusions:

  • A unified approach based on efficient coding and Bayesian inference provides a powerful lens for understanding human decision biases.
  • The proposed computational framework offers a parsimonious explanation for complex decision-making phenomena.