Deterministic Artifact Identity
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| Format: | Recurso digital |
| Sprache: | Englisch |
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Zenodo
2026
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| _version_ | 1866901131869814784 |
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| author | Kopcho, Rich |
| author_facet | Kopcho, Rich |
| contents | <p> This technical note addresses a fundamental challenge in autonomous computational systems: how to uniquely identify<br> artifacts in ways that reflect their computational origins rather than arbitrary system assignments.</p> <p> The note proposes that artifact identity be derived deterministically from the computation that produced it and the<br> artifacts used as inputs. Under this scheme, identical computations using identical inputs always produce identical<br> artifact identities — making it impossible to have two different artifacts with the same identity, or two instances of<br> the same computation with different identities.</p> <p> Traditional systems identify outputs arbitrarily using file paths, random strings, or database keys, making it<br> impossible to verify computational lineage or validate artifact graphs. Deterministic identity resolves this by<br> enabling verification of computational results through re-execution, artifact reuse across independent distributed<br> systems, and the accumulation of computational work rather than its repetition. Multiple independent systems can<br> contribute to a shared artifact graph, building upon prior computation rather than recreating it.</p> <p> This is Technical Note 06 of the Agent Artifact Availability (AAA) Framework series.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19059436 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Deterministic Artifact Identity Kopcho, Rich agent artifact availability, cumulative computing, computational artifacts, AI agents, distributed systems, artifact persistence <p> This technical note addresses a fundamental challenge in autonomous computational systems: how to uniquely identify<br> artifacts in ways that reflect their computational origins rather than arbitrary system assignments.</p> <p> The note proposes that artifact identity be derived deterministically from the computation that produced it and the<br> artifacts used as inputs. Under this scheme, identical computations using identical inputs always produce identical<br> artifact identities — making it impossible to have two different artifacts with the same identity, or two instances of<br> the same computation with different identities.</p> <p> Traditional systems identify outputs arbitrarily using file paths, random strings, or database keys, making it<br> impossible to verify computational lineage or validate artifact graphs. Deterministic identity resolves this by<br> enabling verification of computational results through re-execution, artifact reuse across independent distributed<br> systems, and the accumulation of computational work rather than its repetition. Multiple independent systems can<br> contribute to a shared artifact graph, building upon prior computation rather than recreating it.</p> <p> This is Technical Note 06 of the Agent Artifact Availability (AAA) Framework series.</p> |
| title | Deterministic Artifact Identity |
| topic | agent artifact availability, cumulative computing, computational artifacts, AI agents, distributed systems, artifact persistence |
| url | https://doi.org/10.5281/zenodo.19059436 |