Natural language syntax complies with the free-energy principle
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Summary
This summary is machine-generated.This study connects natural language syntax to the free-energy principle (FEP) through active inference. It proposes Turing-Chomsky Compression (TCC) to explain efficient syntactic computation as a form of self-organization.
Area Of Science
- Computational neuroscience
- Theoretical linguistics
- Psycholinguistics
Background
- Natural language syntax generates complex, hierarchical structures.
- The free-energy principle (FEP) explains how biological systems maintain organization.
- Previous work linked FEP to speech segmentation and linguistic communication.
Purpose Of The Study
- Extend the FEP to explain the computations underlying syntactic object generation.
- Argue that language design principles, like "minimal search," align with the FEP.
- Introduce Turing-Chomsky Compression (TCC) as a principle for efficient syntactic computation.
Main Methods
- Conceptual integration of theoretical syntax and the FEP.
- Modeling syntactic computations within the FEP framework.
- Using tree-geometric depth and Kolmogorov complexity (Lempel-Ziv) for preliminary analysis.
Main Results
- Principles of economy in language design adhere to the FEP.
- Tree-geometric depth and Kolmogorov complexity predict syntactic operations aligned with variational free energy minimization.
- TCC provides a principle for efficient syntactic computation.
Conclusions
- The FEP offers a powerful framework for understanding higher language functions and computability in linguistics.
- TCC unifies linguistic concerns with the FEP's account of self-organization.
- Evidence from linguistics and psycholinguistics supports grounding syntactic computation in active inference.
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