Evidence map›Paper›PMID 38706520›Full record

ArticleSynthese2024

Natural language syntax complies with the free-energy principle.

Elliot Murphy, Emma Holmes, Karl Friston

Abstract read
In one paragraph

Article in Synthese, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Elliot MurphyVivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center, Houston, TX 77030 USA.ORCID 0000-0003-1456-0343
Emma HolmesDepartment of Speech Hearing and Phonetic Sciences, University College London, London, WC1N 1PF UK.
Karl FristonThe Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, WC1N 3AR UK.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating syntactic objects. We argue that recently proposed principles of economy in language design-such as "minimal search" criteria from theoretical syntax-adhere to the FEP. This affords a greater degree of explanatory power to the FEP-with respect to higher language functions-and offers linguistics a grounding in first principles with respect to computability. While we mostly focus on building new principled conceptual relations between syntax and the FEP, we also show through a sample of preliminary examples how both tree-geometric depth and a Kolmogorov complexity estimate (recruiting a Lempel-Ziv compression algorithm) can be used to accurately predict legal operations on syntactic workspaces, directly in line with formulations of variational free energy minimization. This is used to motivate a general principle of language design that we term Turing-Chomsky Compression (TCC). We use TCC to align concerns of linguists with the normative account of self-organization furnished by the FEP, by marshalling evidence from theoretical linguistics and psycholinguistics to ground core principles of efficient syntactic computation within active inference.

Indexed as

Active inferenceCompressionFree-energy principleKolmogorov complexityLanguageLempel–Ziv

Identifiers

PMID38706520
PMCPMC11068586

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.