Astorga, E. F. S. and Letelier, Juan Carlos (2026) Anticipation and Structural Coupling: Two Sides of the Same Coin. [Preprint]
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Abstract
Two foundational frameworks in theoretical biology, namely Maturana’s Structural Coupling and Rosen’s Anticipatory Systems, developed in mutual isolation despite addressing the same phenomenon. We argue that Structural Coupling is precisely the historical process by which an organism becomes an anticipatory system: the process by which the regulatory subnetwork’s dynamics come into conjugacy with relevant environmental dynamics. We show that the components of Rosen’s anticipatory architecture map onto the autopoietic system in a way that satisfies all of Rosen’s formal conditions.
Furthermore, a conditional probability matrix describing the regulatory subnetwork is actually the observer’s statistical redescription of a bona fide dynamical system. Because organisms co-constitute rather than merely predict their environments, Rosen’s concordance condition must be reformulated as a fixed-point condition. This synthesis carries direct consequences for Artificial Life: current AI systems, including LLMs, are reactive in Rosen’s precise sense and incapable
of Umwelt construction; open-ended evolution requires true anticipatory agents. A criterion is provided.
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| Item Type: | Preprint | |||||||||
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| Keywords: | Anticipation, Structural Coupling, Robert Rosen, Humberto Maturana, Cognition, LLM, Artificial Intelligence, Artificial Life | |||||||||
| Subjects: | Specific Sciences > Biology Specific Sciences > Complex Systems Specific Sciences > Cognitive Science Specific Sciences > Computer Science Specific Sciences > Artificial Intelligence |
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| Depositing User: | Enrique F. Soto Astorga | |||||||||
| Date Deposited: | 10 Apr 2026 13:04 | |||||||||
| Last Modified: | 10 Apr 2026 13:04 | |||||||||
| Item ID: | 29005 | |||||||||
| Subjects: | Specific Sciences > Biology Specific Sciences > Complex Systems Specific Sciences > Cognitive Science Specific Sciences > Computer Science Specific Sciences > Artificial Intelligence |
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| Date: | April 2026 | |||||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/29005 |
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