An Ansatz for Computational Undecidability in RNA Automata.

Automata RNA automata Turing’s oracle novelty generation self-reference undecidability

Journal

Artificial life
ISSN: 1530-9185
Titre abrégé: Artif Life
Pays: United States
ID NLM: 9433814

Informations de publication

Date de publication:
01 05 2023
Historique:
medline: 16 6 2023
pubmed: 6 8 2022
entrez: 5 8 2022
Statut: ppublish

Résumé

In this ansatz we consider theoretical constructions of RNA polymers into automata, a form of computational structure. The bases for transitions in our automata are plausible RNA enzymes that may perform ligation or cleavage. Limited to these operations, we construct RNA automata of increasing complexity; from the Finite Automaton (RNA-FA) to the Turing machine equivalent 2-stack PDA (RNA-2PDA) and the universal RNA-UPDA. For each automaton we show how the enzymatic reactions match the logical operations of the RNA automaton. A critical theme of the ansatz is the self-reference in RNA automata configurations that exploits the program-data duality but results in computational undecidability. We describe how computational undecidability is exemplified in the self-referential Liar paradox that places a boundary on a logical system, and by construction, any RNA automata. We argue that an expansion of the evolutionary space for RNA-2PDA automata can be interpreted as a hierarchical resolution of computational undecidability by a meta-system (akin to Turing's oracle), in a continual process analogous to Turing's ordinal logics and Post's extensible recursively generated logics. On this basis, we put forward the hypothesis that the resolution of undecidable configurations in RNA automata represent a novelty generation mechanism and propose avenues for future investigation of biological automata.

Identifiants

pubmed: 35929772
pii: 112511
doi: 10.1162/artl_a_00370
doi:

Substances chimiques

RNA 63231-63-0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

261-288

Informations de copyright

© 2023 Massachusetts Institute of Technology.

Auteurs

Adam J Svahn (AJ)

University of Sydney, Faculty of Engineering, Centre for Complex Systems, Faculty of Medicine and Health, Westmead Clinical School. adam.svahn@sydney.edu.au.

Mikhail Prokopenko (M)

University of Sydney, Faculty of Engineering, Centre for Complex Systems, Sydney Institute for Infectious Diseases.

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Classifications MeSH