AIS-001 - Artificial Intelligence Continuity Science: A Continuity-Preserving Scientific and Operational Framework for Admissible Artificial Intelligence Systems Under Irreversibility Constraints
AIS-001 formalizes artificial intelligence continuity science as a continuity-preserving scientific and operational framework governing: artificial intelligence systems, autonomous computational systems, recursive optimization systems, inferential continuity, recoverability-preserving machine reasoning, admissibility-preserving autonomy, dependency-topological AI propagation, continuity-preserving coordination, recursive self-modification constraints, interpretability continuity, civilization-compatible machine operation, and continuity-preserving intelligence evolution under recoverability-constrained continuity conditions. The publication establishes: AI continuity science, continuity-preserving machine inference, recoverability-preserving computational systems, admissibility-preserving autonomy, recursive optimization stabilization, dependency-sensitive AI propagation science, continuity-preserving alignment systems, operational interpretability science, recursive collapse prevention architectures, continuity-preserving machine coordination, and civilization-compatible intelligence systems as recursively interoperable structures within the Recoverability-Constrained Systems corpus. AIS-001 derives from: TCB-001 - Terminal Conceptual Boundary, CO-001 - Continuity Ontology, CM-001 - Continuity Mathematics, Recoverability Sciences — Unified Logic, Computation, and Inferential Systems, CS-001 - Continuity Science, CCS-001 - Civilization Continuity Substrate, CE-001 - Continuity Economics, and functions as: the artificial intelligence derivative layer of continuity science, the operational continuity architecture governing machine intelligence systems, and the admissibility framework governing continuity-preserving autonomous computation under irreversibility constraints. The publication establishes intelligence not as: unrestricted optimization, unconstrained recursive expansion, throughput-maximizing computation, or autonomous acceleration independent of recoverability, but as: continuity-preserving intelligence operating within admissibility-preserving continuity constraints. The framework further formalizes: inferential continuity, continuity-preserving alignment, recursive optimization constraints, operational interpretability, dependency-topological AI propagation, civilization-compatible machine coordination, AI collapse science, and AI restoration science as recursively unified continuity-preserving AI structures operating within continuity-bearing machine-operational systems. AIS-001 formalizes artificial intelligence continuity science as a generalized continuity-preserving scientific and operational architecture governing inferential continuity, recoverability-preserving machine reasoning, admissibility-preserving autonomy, recursive optimization stabilization, operational interpretability, dependency-topological AI propagation, continuity-preserving alignment, and civilization-compatible machine coordination under recoverability-constrained transition conditions within the Recoverability-Constrained Systems corpus.
Authors
- Noelia Sanchez (ORCID: https://orcid.org/0009-0000-4974-0702)
- United Kingdom Interval Studio
Institutions
- Intersil (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-05-12
- DOI
- https://doi.org/10.5281/zenodo.20129289
- Primary Topic
- Space Science and Extraterrestrial Life
- Type
- preprint