Causal Information Exchange as a Necessary Condition for Adaptive Regulation: A Perturbational Framework for Life and Agency
Abstract
Information exchange can support living organisation without providing a sufficient criterion for life. We develop a perturbational framework that distinguishes causal transmission, directional imbalance, internal retention, response structure and functional regulation. Randomised interventions define Shannon information channels; for deterministic binary recipients, their context-conditioned mutual information is exactly a paired perturbation-response indicator. Spatial and temporal averages of these local channels measure information-exposure density, rather than joint information or conserved information flux. Complementary Coding Theorem Method and Block Decomposition Method (BDM) estimates describe response and trajectory structure. A same-shaped zero-mask reference separates raw BDM from a structural contrast; neither is a channel mutual information. Retained exploratory BDM plots are distinguished from the normalised causal-channel results. Retention-weighted coupling and directionality obey algebraic bounds, and ensemble reciprocity need not imply reciprocity within individual contexts. For a specified binary sensor--internal-channel--actuator task, we derive a positive information lower bound from successful regulation and construct controllers with identical information profiles but opposite functional outcomes. A study of 2,000 ordered elementary-cellular-automaton rule pairs, six detailed examples, recurrence and lossless coding analyses, and a signed-network extension demonstrates dissociations among perturbational responsiveness, structural regularity and recurrence. The results establish causal information as a necessary resource for the stated form of adaptive regulation, while showing why neither causal coupling nor response complexity alone measures agency or life.
Related
- A Simple Necessary and Sufficient Condition for Yang--Baxter Integrability
- A target-domain augmentation and class-wise alignment framework for few-shot cross-condition bearing fault diagnosis
- The Universe as a Consistency-Constrained Information History: An Interpretive Framework (Akashic Ledger Architecture Cosmology)
- Information limits of photonic lantern wavefront sensing: a Fisher- and quantum-Fisher-information framework and its relation to Fourier-filtering sensitivity limits
- Fisher Information Dynamics: A Kinematic Framework for Phase Space Ordering with Applications to Shock Layers and Turbulence
BibTeX
@misc{luvalle2026causal,
title = {{Causal Information Exchange as a Necessary Condition for Adaptive Regulation: A Perturbational Framework for Life and Agency}},
author = {Brian LuValle and Abicumaran Uthamacumaran and Hector Zenil},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.24017},
eprint = {2610.24017},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.24017},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Causal Information Exchange as a Necessary Condition for Adaptive Regulation: A Perturbational Framework for Life and Agency
AU - Brian LuValle
AU - Abicumaran Uthamacumaran
AU - Hector Zenil
PY - 2026
DA - 2026/10/16
PB - arXiv
DO - 10.48550/arxiv.2610.24017
UR - https://arxiv.org/abs/2610.24017
AB - Information exchange can support living organisation without providing a sufficient criterion for life. We develop a perturbational framework that distinguishes causal transmission, directional imbalance, internal retention, response structure and functional regulation. Randomised interventions define Shannon information channels; for deterministic binary recipients, their context-conditioned mutual information is exactly a paired perturbation-response indicator. Spatial and temporal averages of these local channels measure information-exposure density, rather than joint information or conserved information flux. Complementary Coding Theorem Method and Block Decomposition Method (BDM) estimates describe response and trajectory structure. A same-shaped zero-mask reference separates raw BDM from a structural contrast; neither is a channel mutual information. Retained exploratory BDM plots are distinguished from the normalised causal-channel results. Retention-weighted coupling and directionality obey algebraic bounds, and ensemble reciprocity need not imply reciprocity within individual contexts. For a specified binary sensor--internal-channel--actuator task, we derive a positive information lower bound from successful regulation and construct controllers with identical information profiles but opposite functional outcomes. A study of 2,000 ordered elementary-cellular-automaton rule pairs, six detailed examples, recurrence and lossless coding analyses, and a signed-network extension demonstrates dissociations among perturbational responsiveness, structural regularity and recurrence. The results establish causal information as a necessary resource for the stated form of adaptive regulation, while showing why neither causal coupling nor response complexity alone measures agency or life.
ER -