LOGOS-CA: A Cellular Automaton Using Natural Language as State and Rule

Fuente: arXiv
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Autore principale: Utimula, Keishu
Natura: Preprint
Pubblicazione: 2026
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author Utimula, Keishu
author_facet Utimula, Keishu
contents Large Language Models (LLMs), trained solely on massive text data, have achieved high performance on the Winograd Schema Challenge (WSC), a benchmark proposed to measure commonsense knowledge and reasoning abilities about the real world. This suggests that the language produced by humanity describes a significant portion of the world with considerable nuance. In this study, we attempt to harness the high expressive power of language within cellular automata. Specifically, we express cell states and rules in natural language and delegate their updates to an LLM. Through this approach, cellular automata can transcend the constraints of merely numerical states and fixed rules, providing us with a richer platform for simulation. Here, we propose LOGOS-CA (Language Oriented Grid Of Statements - Cellular Automaton) as a natural framework to achieve this and examine its capabilities. We confirmed that LOGOS-CA successfully performs simple forest fire simulations and also serves as an intriguing subject for investigation from an Artificial Life (ALife) perspective. In this paper, we report the results of these experiments and discuss directions for future research using LOGOS-CA.
format Preprint
id arxiv_https___arxiv_org_abs_2602_00036
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle LOGOS-CA: A Cellular Automaton Using Natural Language as State and Rule
Utimula, Keishu
Cellular Automata and Lattice Gases
Artificial Intelligence
Formal Languages and Automata Theory
Neural and Evolutionary Computing
Large Language Models (LLMs), trained solely on massive text data, have achieved high performance on the Winograd Schema Challenge (WSC), a benchmark proposed to measure commonsense knowledge and reasoning abilities about the real world. This suggests that the language produced by humanity describes a significant portion of the world with considerable nuance. In this study, we attempt to harness the high expressive power of language within cellular automata. Specifically, we express cell states and rules in natural language and delegate their updates to an LLM. Through this approach, cellular automata can transcend the constraints of merely numerical states and fixed rules, providing us with a richer platform for simulation. Here, we propose LOGOS-CA (Language Oriented Grid Of Statements - Cellular Automaton) as a natural framework to achieve this and examine its capabilities. We confirmed that LOGOS-CA successfully performs simple forest fire simulations and also serves as an intriguing subject for investigation from an Artificial Life (ALife) perspective. In this paper, we report the results of these experiments and discuss directions for future research using LOGOS-CA.
title LOGOS-CA: A Cellular Automaton Using Natural Language as State and Rule
topic Cellular Automata and Lattice Gases
Artificial Intelligence
Formal Languages and Automata Theory
Neural and Evolutionary Computing
url https://arxiv.org/abs/2602.00036