Published October 26, 2026 | Version 2.0
Preprint Open

A Self-Configuring Symbiotic Network of Minimal State Nodes

Authors/Creators

Description

Japanese and English editions of the same concept paper, version 2.0. Not peer reviewed. No new simulation or experimental results are reported.

This version extends and reorganizes version 1.0 (7 October 2026) around minimal state nodes, self-configuration inspired by flagellar mechanisms, network-level information continuity, and in-body symbiosis.

English abstract

This paper proposes a collection of locally interacting state nodes that functions as one communication network, one storage system, and one computing system, and connects this form of information processing to long-term symbiosis with the body and nervous system. Its basic node is not a complete AI or computer. It is described through distinguishable states, interaction ports, a local transition rule, and resource constraints. "Minimal" refers to functional minimality relative to a task and observational granularity; it does not denote a specific physical size or number of molecules.

Drawing on the switching of export substrates during flagellar assembly and on changes in motor composition that depend on mechanical load, the paper abstracts two design principles: prerequisite-dependent functional activation and participation or withdrawal in response to local load. Integration of the three functions centers on the same node states and interaction relations contributing to information transmission, history retention, and changes in subsequent processing. Structural recovery, functional recovery, and information continuity are distinguished, and conditions for using retained histories despite component replacement are identified. Valid observations of no change are also distinguished from absent measurements, non-arrival, and faults.

Artificial molecular structures within the body are positioned as one possible implementation of this general model. "Mitochondria-like" is a metaphor for functional symbiosis, in which a function becomes part of the host's own functioning; it does not constrain morphology. The framework allows collaboration with external AI while connecting locally retained memory and computation, mutual learning between the artificial system and the nervous system, component turnover, and the person's continuing ability to reconsider use.

The contribution is a conceptual framework linking the basic unit, local rules, network-level functions, and the relationship with the body. It does not demonstrate implementation, performance, or realization within the body. Requirements are distinguished from hypotheses to be examined through comparison, and research questions are formulated for subsequent specialist investigation.

日本語要旨

本稿は、局所的に相互作用する状態ノードの集合を、一つの通信網、一つの保存装置、一つの計算装置として働かせ、その情報処理を身体・神経系との長期的な共生へ接続する構想を提案する。基本単位となるノードは、単独で完成したAIや計算機ではなく、区別可能な状態、相互作用口、局所遷移規則、資源制約によって記述する。「最小」は対象課題と観測粒度に対する機能的な最小性を指し、特定の物理寸法や分子数を意味しない。

べん毛モーターの組立段階に伴う輸送対象の切替と、機械的負荷に依存する構成変化を参照し、前提条件付きの機能有効化と、局所負荷に応じた参加・離脱を設計原理として抽象化する。ノードの状態と接続関係が、情報の伝達、履歴の保持、後続処理の変更に共通して関与することを、三機能統合の中心に置く。構造回復、機能回復、情報継続を区別し、構成単位が交換されても履歴を利用し続けられる条件を整理する。また、有効に観測された無変化を、未測定・未着・故障と区別する。

身体内の人工分子構造は、この一般モデルの実装候補として位置づける。「ミトコンドリア様」は機能を宿主自身の働きへ取り込む共生関係の比喩であり、形態を限定しない。外部AIとの協働を許容しつつ、身体側に記憶と計算が残ること、神経系と人工系の相互学習、構成単位の更新、本人が利用を選び直せることを一つの枠組みに接続する。

本稿の成果は、基本単位、局所規則、網としての機能、身体との関係をつなぐ概念枠組みの提示である。実装、性能、身体内での成立を実証したものではない。成立要件と比較によって検討する仮説を分け、後続の専門研究が引き継げる課題を示す。

Files: self-configuring-symbiotic-network-ja-v2.0.pdf (Japanese); self-configuring-symbiotic-network-en-v2.0.pdf (English).

Author: imbolc. No affiliation listed. License: CC BY 4.0. ChatGPT and Codex assisted with drafting, translation, and editing; AI is not listed as an author.

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Additional details

Additional titles

Alternative title (Japanese)
最小状態ノードによる自己構成型共生網

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