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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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The Boolean Language of Thought is recoverable from learning data.

Fausto Carcassi1, Jakub Szymanik2

  • 1Department of Linguistics, University of Tübingen, Keplerstraße 2, 72074 Tübingen, Germany.

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Summary

Researchers explored the Language of Thought Hypothesis (LoTH), finding that human Boolean cognitive representations can be recovered from experimental data. The success of this recovery depends on experimental design and the complexity of the cognitive system.

Keywords:
Bayesian inferenceCategory learningLanguage of Thought HypothesisParameter recovery simulation

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Area of Science:

  • Cognitive Science
  • Philosophy of Mind
  • Computational Linguistics

Background:

  • The Language of Thought Hypothesis (LoTH) posits that human cognition relies on symbolic reasoning within a formal language.
  • Key aspects of LoTH include concepts as expressions, deduction as syntactic manipulation, and learning as inference.

Purpose of the Study:

  • To investigate the extent to which human "Language of Thought" (LoT) can be recovered from experimental data.
  • To focus on the fragment of LoT representing Boolean categories and simulate its recovery.

Main Methods:

  • Simulated category learning experiments to test the recoverability of Boolean LoTs.
  • Focused on recovering the structure of Boolean representations from behavioral data.

Main Results:

  • Demonstrated that the vast majority of Boolean LoTs can be accurately recovered in principle from experimental data.
  • Found that the success of LoT recovery is critically dependent on the experimental design.
  • Observed that LoTs with fewer operators are recovered more rapidly from category learning data.

Conclusions:

  • It is possible in principle to recover human Boolean "Language of Thought" representations from experimental data.
  • Experimental design is a crucial factor influencing the accuracy and efficiency of LoT recovery.
  • Simpler cognitive architectures (fewer operators) facilitate faster inference of the "Language of Thought".