Complexity of Fungal Automaton Prediction

Fuente: arXiv
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Autori principali: Formenti, Enrico, Goles, Eric, Perrot, Kévin, Ríos-Wilson, Martín, Ruiz-Tala, Domingo
Natura: Preprint
Pubblicazione: 2026
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author Formenti, Enrico
Goles, Eric
Perrot, Kévin
Ríos-Wilson, Martín
Ruiz-Tala, Domingo
author_facet Formenti, Enrico
Goles, Eric
Perrot, Kévin
Ríos-Wilson, Martín
Ruiz-Tala, Domingo
contents Fungal automata are a nature-inspired computational model, where a rule is alternatively applied verticaly and horizontaly. In this work we study the computational complexity of predicting the dynamics of all fungal freezing totalistic one-dimentional rules of radius $1$, exhibiting various behaviors. Despite efficiently predictable in most cases (with non-deterministic logspace algorithms), a non-linear rule is left open to characterize. We further explore the freezing majority rule (which is totalistic), and prove that at radius $1.5$ it becomes $\mathbf{P}$-complete to predict.
format Preprint
id arxiv_https___arxiv_org_abs_2604_15177
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Complexity of Fungal Automaton Prediction
Formenti, Enrico
Goles, Eric
Perrot, Kévin
Ríos-Wilson, Martín
Ruiz-Tala, Domingo
Computational Complexity
Formal Languages and Automata Theory
Fungal automata are a nature-inspired computational model, where a rule is alternatively applied verticaly and horizontaly. In this work we study the computational complexity of predicting the dynamics of all fungal freezing totalistic one-dimentional rules of radius $1$, exhibiting various behaviors. Despite efficiently predictable in most cases (with non-deterministic logspace algorithms), a non-linear rule is left open to characterize. We further explore the freezing majority rule (which is totalistic), and prove that at radius $1.5$ it becomes $\mathbf{P}$-complete to predict.
title Complexity of Fungal Automaton Prediction
topic Computational Complexity
Formal Languages and Automata Theory
url https://arxiv.org/abs/2604.15177