State-Dependent Informational Substitution in Memory and Prediction
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| Format: | Recurso digital |
| Sprache: | Englisch |
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2026
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| _version_ | 1866902188429672448 |
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| author | Cappello, Nicola |
| author_facet | Cappello, Nicola |
| contents | <p>This preprint introduces the SIDSMP framework (State-Dependent Informational Substitution in Memory and Prediction), a constraint-based dynamical model in which predictive structure emerges, stabilizes, and collapses under finite informational and energetic budgets.</p> <p>The model is substrate-independent and does not assume specific neural, biological, or artificial implementations. Instead, it formalizes minimal structural constraints governing transformability, structural work, dissipative cost, and predictive capacity in finite informational systems.</p> <p>The present work is foundational and theoretical. It provides a formal structure, identifies admissible dynamical regimes, and defines falsifiable predictions, while leaving domain-specific operationalization and empirical calibration to future research.</p> <p>A reproducible computational toy model implementing the validation suite is archived separately and linked under Related Identifiers.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18770918 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | State-Dependent Informational Substitution in Memory and Prediction Cappello, Nicola Dynamical systems Information Theory Predictive Systems Resource Constraints Complex Systems State-Dependent Dynamics computational modeling complex systems theoretical framework Active Inference Thermodynamics of Computation Collapse Regimes <p>This preprint introduces the SIDSMP framework (State-Dependent Informational Substitution in Memory and Prediction), a constraint-based dynamical model in which predictive structure emerges, stabilizes, and collapses under finite informational and energetic budgets.</p> <p>The model is substrate-independent and does not assume specific neural, biological, or artificial implementations. Instead, it formalizes minimal structural constraints governing transformability, structural work, dissipative cost, and predictive capacity in finite informational systems.</p> <p>The present work is foundational and theoretical. It provides a formal structure, identifies admissible dynamical regimes, and defines falsifiable predictions, while leaving domain-specific operationalization and empirical calibration to future research.</p> <p>A reproducible computational toy model implementing the validation suite is archived separately and linked under Related Identifiers.</p> |
| title | State-Dependent Informational Substitution in Memory and Prediction |
| topic | Dynamical systems Information Theory Predictive Systems Resource Constraints Complex Systems State-Dependent Dynamics computational modeling complex systems theoretical framework Active Inference Thermodynamics of Computation Collapse Regimes |
| url | https://doi.org/10.5281/zenodo.18770918 |