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Computational rationality: linking mechanism and behavior through bounded utility maximization.

Richard L Lewis1, Andrew Howes, Satinder Singh

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Summary
This summary is machine-generated.

We introduce computational rationality, a framework integrating information-processing limits into rational analysis. This approach models behavior as arising from cognitive mechanisms adapted to environmental and internal constraints, offering new explanations for cognitive processes.

Keywords:
Bounded optimalityBounded rationalityCognitive architectureCognitive modelingRational analysisRationalityUtility maximization

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Area of Science:

  • Cognitive Science
  • Computational Neuroscience
  • Artificial Intelligence

Background:

  • Rational analyses often overlook cognitive limitations.
  • Bounded optimality provides a foundation for incorporating constraints.
  • Understanding mechanism and behavior requires considering internal and external factors.

Purpose of the Study:

  • Propose a framework for rational analysis that includes information-processing bounds.
  • Introduce computational rationality as a novel approach.
  • Develop theories of mechanism and behavior grounded in computational constraints.

Main Methods:

  • Applied bounded optimality to theories of mechanism and behavior.
  • Defined theories as optimal program problems with adaptation environment, bounded machine, and utility function.
  • Illustrated the framework with examples from visual attention, manual response ordering, and reasoning.

Main Results:

  • The framework, computational rationality, integrates computational mechanisms into the definition of rational action.
  • Theories can be specified based on adaptation to bounds versus adaptation to the broader ecology.
  • Demonstrated framework's applicability across diverse cognitive domains.

Conclusions:

  • Computational rationality offers a unified approach to understanding rational action under constraints.
  • The framework provides a spectrum of explanations based on emphasis on bounds or ecology.
  • This approach advances the integration of computational principles into cognitive theories.