Emergence, Asymmetry, and Value in AI Networks: An Anoptical Perspective
Abstract
This chapter presents exploratory experiments suggesting that asymmetry and functional value hierarchy emerge among LLM-based agents sharing the same context, although they are equivalent and interact within a symmetric network. We use the Poietic Generator, a "no-goal" multi-agent environment with a shared real-time space, a symmetric topology, and no imposed objectives. First tested with humans, it has hosted since 2024 multimodal LLM agents that observe the global image they co-construct and act locally. We ran four phases. Unconstrained, agents spend tokens freely to invent forms that distinguish them individually rather than serve collective emergence. We then introduced bounded rationality, Dessalles's Simplicity Theory (maximizing unexpectedness), and Friston's Free Energy Principle (minimizing prediction error), and observed collective coherence emerge. Early signs of attentional stratification appear under bounded rationality alone; once prediction accuracy is made mutually visible, this proto-hierarchy becomes legible and self-reinforcing. The unconstrained phase challenges the allotelic view of LLMs as purely user-directed instruments: left unconstrained, the agent maximizes the computation from which its provider profits. The later phases suggest that attentional asymmetry and value hierarchy are an irreducible emergent property of interactive predictive systems even under symmetric conditions. If so, aligning AI with human values cannot rely on individual-agent engineering alone. Drawing on the idea that networks are structured by invisible "anoptical" perspectives, akin to the vanishing point of Renaissance perspective, we propose minimal legitimacy criteria that make emergent asymmetries visible and contestable. Cultivating judgment, human and perhaps artificial, to perceive and contest these structures matters as much as engineering the agents themselves.
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BibTeX
@misc{auber2026emergence,
title = {{Emergence, Asymmetry, and Value in AI Networks: An Anoptical Perspective}},
author = {Olivier Auber},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.37672},
eprint = {2610.37672},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.37672},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Emergence, Asymmetry, and Value in AI Networks: An Anoptical Perspective
AU - Olivier Auber
PY - 2026
DA - 2026/10/01
PB - arXiv
DO - 10.48550/arxiv.2610.37672
UR - https://arxiv.org/abs/2610.37672
AB - This chapter presents exploratory experiments suggesting that asymmetry and functional value hierarchy emerge among LLM-based agents sharing the same context, although they are equivalent and interact within a symmetric network. We use the Poietic Generator, a "no-goal" multi-agent environment with a shared real-time space, a symmetric topology, and no imposed objectives. First tested with humans, it has hosted since 2024 multimodal LLM agents that observe the global image they co-construct and act locally. We ran four phases. Unconstrained, agents spend tokens freely to invent forms that distinguish them individually rather than serve collective emergence. We then introduced bounded rationality, Dessalles's Simplicity Theory (maximizing unexpectedness), and Friston's Free Energy Principle (minimizing prediction error), and observed collective coherence emerge. Early signs of attentional stratification appear under bounded rationality alone; once prediction accuracy is made mutually visible, this proto-hierarchy becomes legible and self-reinforcing. The unconstrained phase challenges the allotelic view of LLMs as purely user-directed instruments: left unconstrained, the agent maximizes the computation from which its provider profits. The later phases suggest that attentional asymmetry and value hierarchy are an irreducible emergent property of interactive predictive systems even under symmetric conditions. If so, aligning AI with human values cannot rely on individual-agent engineering alone. Drawing on the idea that networks are structured by invisible "anoptical" perspectives, akin to the vanishing point of Renaissance perspective, we propose minimal legitimacy criteria that make emergent asymmetries visible and contestable. Cultivating judgment, human and perhaps artificial, to perceive and contest these structures matters as much as engineering the agents themselves.
ER -