BONNIE'S NOTES

Tag: open-question

9 items with this tag.

  • May 29, 2025

    4E (embodied, embedded, extended, and enactive) cognition

    • topic-cognitive-science
    • seed
    • COGS-UN1001
    • open-question
  • May 28, 2025

    The symbol grounding problem asks how the brain connects mental representations to the external world

    • permanent-note
    • topic-cognitive-science
    • open-question
  • Apr 15, 2025

    Aristotelian vs. Platonic proofs

    • permanent-note
    • topic-logic-mathematics
    • MATH-GU4200
    • open-question
  • Apr 14, 2025

    Paper | Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning

    • literature-note
    • concept-question
    • open-question
  • Apr 08, 2025

    Human infants are coupled in dependency with their caregivers

    • permanent-note
    • topic-cognitive-science
    • open-question
  • Sep 26, 2024

    Chapter | An Interlude About Computers

    • literature-note
    • concept-question
    • open-question
  • May 26, 2024

    Conditioning is the learned association between a behavior and an unrelated stimulus

    • permanent-note
    • topic-cognitive-science
    • open-question
  • May 26, 2024

    Six systems of core knowledge, after Spelke

    • permanent-note
    • topic-cognitive-science
    • open-question
  • Apr 16, 2024

    Taste is rational while disgust is instinctive, after Cortez

    • permanent-note
    • open-question

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Backlinks

  • 4E (embodied, embedded, extended, and enactive) cognition
  • Aristotelian vs. Platonic proofs
  • Conditioning is the learned association between a behavior and an unrelated stimulus
  • Human infants are coupled in dependency with their caregivers
  • Six systems of core knowledge, after Spelke
  • Taste is rational while disgust is instinctive, after Cortez
  • The symbol grounding problem asks how the brain connects mental representations to the external world
  • Chapter | An Interlude About Computers
  • Paper | Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning

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