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Related Concept Videos

Cognitivism01:17

Cognitivism

Cognitive psychology emerged as a significant field in the mid-20th century. It focused on understanding humans' internal mental processes. This approach emphasizes how people perceive, remember, think, and solve problems—elements critical to human cognition.
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Curiosity-driven exploration: foundations in neuroscience and computational modeling.

Alireza Modirshanechi1, Kacper Kondrakiewicz2, Wulfram Gerstner1

  • 1École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

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|November 4, 2023
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Summary
This summary is machine-generated.

Curiosity is the drive to explore the unknown. This review categorizes information-seeking behaviors and explores computational models, integrating diverse studies to demystify curiosity.

Keywords:
informationneural circuitsneuromodulatory systemsnoveltyorientingreinforcement learningsurprise

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Machine Learning

Background:

  • Curiosity is an intrinsic drive to explore the unknown, observed in humans and animals.
  • Existing definitions lack consensus, but curiosity is increasingly viewed as information-seeking, not goal-directed behavior.

Purpose of the Study:

  • To review and categorize existing behavioral and neurophysiological studies on curiosity.
  • To explore recent machine learning computational models of curiosity.
  • To propose an integrated theoretical framework for understanding curiosity.

Main Methods:

  • Phenomenological approach to group studies based on information-seeking types.
  • Review of behavioral and neurophysiological research.
  • Analysis of computational models in machine learning.

Main Results:

  • Categorization of curiosity into three types of information seeking.
  • Identification of machine learning models capable of integrating diverse information-seeking behaviors.
  • Demonstration of how computational models can unify different aspects of curiosity.

Conclusions:

  • A phenomenological and computational approach is crucial for a comprehensive understanding of curiosity.
  • Integrating behavioral, neurophysiological, and computational findings will demystify curiosity.
  • Future research should combine these methodologies to advance the scientific understanding of curiosity.