aiqbench analysis
This research introduces the Cognitive Continuity Test (CCT), a formal framework designed to verify state transitions in persistent AI agents by validating authority, provenance, and belief consolidation. By benchmarking against synthetic transition families, the study establishes methods to distinguish legitimate agent evolution from unauthorized modifications or fabricated interaction histories. The work addresses critical governance challenges for autonomous systems that maintain long-term memory and execute complex tasks across changing environments.
The Cognitive Continuity Test: Verifying Governed State Transitions in Persistent AI Agents
arXiv:2610.00132v1 Announce Type: cross Abstract: Persistent AI agents revise beliefs, consolidate memory, and replace execution substrates. Similar successor states can accompany differently authorized transition claims, while legitimate development can change state substantially. We introduce the Cognitive Continuity Test (CCT), a policy-relative contract for verifying submitted transitions using scoped authority, provenance, deterministic application, semantic predicates, and candidate-persistence receipts. CCT distinguishes verified admissibility, affirmative violation, and unresolved required evidence. Separation results concern transition claims rather than live runtime identity; soundness is conditional on the specified checker and evaluator assumptions. IdentityLineageBench provides 24 generated transition families. The reference post-resolution verifier matches all 576 canonical held-out labels; lexical state similarity and a lineage-only diagnostic baseline admit 60.0% and 80.0% of invalid fixtures. These comparisons establish synthetic conformance, not superiority to a policy-aware deployed system. Signed adversarial regressions cover fabricated interaction counts, unsupported belief changes, and mixed missing/contradictory evidence. SIT behavior and actual model migration remain unmeasured. An 18,000-execution valid-path study measures a 6.21 ms default median on resident inputs. We specify the additional activation and recovery obligations needed for deployment.
Abstract:Persistent AI agents revise beliefs, consolidate memory, and replace execution substrates. Similar successor states can accompany differently authorized transition claims, while legitimate development can change state substantially. We introduce the Cognitive Continuity Test (CCT), a policy-relative contract for verifying submitted transitions using scoped authority, provenance, deterministic application, semantic predicates, and candidate-persistence receipts. CCT distinguishes verified admissibility, affirmative violation, and unresolved required evidence. Separation results concern transition claims rather than live runtime identity; soundness is conditional on the specified checker and evaluator assumptions. IdentityLineageBench provides 24 generated transition families. The reference post-resolution verifier matches all 576 canonical held-out labels; lexical state similarity and a lineage-only diagnostic baseline admit 60.0% and 80.0% of invalid fixtures. These comparisons establish synthetic conformance, not superiority to a policy-aware deployed system. Signed adversarial regressions cover fabricated interaction counts, unsupported belief changes, and mixed missing/contradictory evidence. SIT behavior and actual model migration remain unmeasured. An 18,000-execution valid-path study measures a 6.21 ms default median on resident inputs. We specify the additional activation and recovery obligations needed for deployment.
17 pages, 2 figures, 3 tables. Includes formal proofs, transition taxonomy, and benchmark schema appendices. Reference verifier and reproducible evaluation artifacts available at this https URL
Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI)
arXiv:2610.00132 [cs.CR]
(or arXiv:2610.00132v1 [cs.CR] for this version)
https://doi.org/10.48550/arXiv.2610.00132 arXiv-issued DOI via DataCite (pending registration)
Full text under the publisher's open licence · 219 words
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