Mechanism
The cognition disclosure does not treat observation staleness as a single time-to-live counter attached to a record. It treats staleness as a governed property of accumulated knowledge, managed through the experiential observation store. The experiential observation store is a governed, persistent knowledge structure that accumulates observations derived from the agent's interaction history. Each observation is recorded as a structured entry comprising at least the observation content, the interaction context in which the observation was acquired, a timestamp, an evidential weight reflecting the evidential strength of the observation at the time of recording, and a set of semantic tags enabling domain-indexed retrieval.
Staleness is expressed through the evidential weight rather than through a binary expired flag. Each observation carries a governed evidential weight that may increase or decrease over time based on subsequent observations. The store persists across interactions and across execution substrates as part of the agent's carried cognitive state, so the question the architecture answers is not simply whether an observation has expired, but whether its accumulated evidential support still justifies its participation in a decision.
Evidential Weight as the Staleness Signal
When a new observation corroborates an existing observation, providing independent evidential support for the same conclusion, the existing observation's evidential weight is increased through a governed aggregation function. When a new observation contradicts an existing observation, a contradiction record is created linking the conflicting entries, and the evidential weights of both observations are adjusted according to a governed resolution policy. That resolution policy may consider recency, source reliability, corroboration count, and the cognitive domain field values at the time each observation was recorded. Contradiction records are themselves persisted in the store and are available to the decision evaluation mechanism as evidence of epistemic uncertainty in a particular domain.
Because weight rises with corroboration and is reconsidered on contradiction, a recent observation does not automatically dominate an older one. Recency is one input to the resolution policy, not the deciding factor. This is the structural counterweight the disclosure describes: an observation accumulated over the agent's interaction history carries a governed evidential weight that is not diminished simply by the arrival of a more recent competing observation.
Temporal Decay and Pruning
Staleness is realized through temporal decay and non-retrieval rather than through a wall-clock expiration timestamp. Observations whose evidential weights have decayed below a policy-defined relevance threshold, through temporal decay or repeated non-retrieval, are pruned from the active observation store. A pruned observation is archived in the agent's lineage as a deprecated observation: available for forensic reconstruction but excluded from active evidential retrieval. The mechanism is reversible in the sense that the deprecated entry is preserved, not destroyed, so a later audit can reconstruct exactly what the agent knew and when.
The governing parameters are policy objects, not hard-coded constants. The experiential observation store is subject to governance: the maximum number of retained observations, the retention duration, the evidential weight aggregation function, and the contradiction resolution policy are defined as governance policy objects and recorded in the agent's lineage. The disclosure does not specify numeric retention durations or decay rates; those are deployment-configured policy parameters.
Governed Knowledge Consolidation
Pruning of stale observations occurs as part of governed knowledge consolidation performed during the agent's dream state, an idle-time process. During consolidation the coherence engine evaluates the observation store for structural inefficiencies that degrade evidential retrieval quality over time. Duplicate observations that encode the same semantic content with independent evidential weights are merged into a single observation whose evidential weight reflects the combined corroboration. Contradictory observations whose conflict has persisted beyond a policy-defined duration without resolution are escalated to a governed contradiction resolution process that evaluates the relative evidential weights, recency, source reliability, and contextual consistency of the conflicting observations.
Consolidation also defines a class of knowledge that is deliberately exempt from staleness. Observations whose evidential weights exceed a policy-defined promotion threshold, indicating high corroboration, high retrieval frequency, and sustained relevance across diverse interaction contexts, are promoted to the agent's core knowledge. Core knowledge is a persistent subset of the store that receives preferential retrieval priority and is exempt from temporal decay. Each consolidation action, each merge, deprecation, promotion, and contradiction resolution, is recorded in the agent's lineage as a governed knowledge event.
Freshness in the Capability Layer
The capability-awareness layer applies a complementary freshness discipline to the substrate it evaluates. Capability envelopes are dynamic data objects updated in response to changes in the substrate's structural characteristics: when hardware is provisioned or deprovisioned, when models are loaded or unloaded, when network conditions change, or when other agents consume or release shared substrate resources. The disclosure states the design intent directly: the system does not rely on stale or statically configured capability information, and the capability envelope is a living description of the substrate's present affordances.
Before a capability execution plan is committed, the execution synthesis subsystem performs a pre-commitment validation that re-evaluates the capability determination and the temporal executability forecast to verify that the conditions which obtained when synthesis was initiated continue to obtain. If a substrate resource that was available when synthesis began has since been consumed, or if the temporal window has narrowed below the estimated execution duration, the pre-commitment validation may abort the synthesis and return a non-synthesis determination. This guards against synthesis based on conditions that are no longer current.
Detecting Stale Capability Data
The capability layer also addresses misreported capability, the condition in which a substrate's advertised envelope does not reflect its actual structural characteristics. The disclosure enumerates stale envelope data, data not updated following a configuration change, among the causes of misreporting, alongside software bugs, undetected hardware degradation, and deliberate adversarial misreporting. The system detects misreporting through execution-time validation: when a capability execution plan is submitted, the execution runtime monitors whether the substrate's actual behavior conforms to the envelope used during evaluation. On a detected discrepancy the system records a capability discrepancy event, marks the affected dimensions of the envelope as unreliable, and triggers re-evaluation of all capability determinations that relied on those dimensions.
Forecast accuracy is maintained by the same continuous-comparison principle. The system compares forecasted temporal executability windows against actual executability observations and computes a forecast accuracy metric for each substrate-dimension pair. When accuracy for a pair falls below a configured threshold, the system recalibrates its temporal projection model for that pair by adjusting trend parameters, increasing uncertainty bounds, or replacing the model with a more conservative one.
Policy Freshness Across Suspension
A related freshness mechanism governs the policy under which an agent acts. When a semantic agent resumes execution after an asynchronous interval and detects that the governance policy in force at suspension has been superseded by a newer policy, the confidence governor evaluates policy freshness as a confidence input. Stale policy, a policy whose validity window has expired or whose issuing authority has published a superseding policy, produces a confidence reduction proportional to the governance significance of the policy change. If that reduction causes the confidence value to fall below the execution authorization threshold, the agent transitions to a non-executing cognitive mode and generates an inquiry requesting the current policy before resuming execution. Here staleness is metered through confidence, not through a contribution that is forced to zero.
Distinction From Conventional Staleness Handling
Conventional distributed systems treat capability information as static or as inferred from resource availability at dispatch time, and they treat the inability to act as a failure requiring error handling rather than as a structurally valid result. They do not maintain a persistent, governed body of accumulated observations whose individual evidential weights decay, are corroborated, are contradicted, and are consolidated under policy. The mechanisms disclosed here treat staleness as a continuous, governed, audit-recorded property: evidential weight that rises with corroboration and decays with non-retrieval, pruning to lineage rather than deletion, a core-knowledge class exempt from decay, a living capability envelope validated at the moment of commitment, and policy freshness metered through confidence. Every staleness decision is recorded in the agent's lineage, so the freshness state of any input can be reconstructed after the fact.
Disclosure Scope
Observation staleness handling is disclosed in United States Patent Application 19/647,395. The disclosure includes the experiential observation store with its per-observation evidential weight, timestamp, and semantic tags; the governed aggregation and contradiction-resolution policies that raise and lower evidential weight; temporal decay and repeated non-retrieval as the path to a policy-defined relevance threshold; pruning of below-threshold observations to lineage as deprecated, forensically retained entries; the dream-state knowledge consolidation that merges duplicates, resolves persistent contradictions, and promotes high-weight observations to a core-knowledge class exempt from temporal decay; the living capability envelope and its pre-commitment validation; detection of stale envelope data through execution-time misreporting validation and forecast recalibration; and policy freshness evaluated as a confidence input by the confidence governor on resumption after suspension. The retention durations, decay rates, relevance thresholds, and promotion thresholds referenced are policy-defined parameters configured per deployment and recorded in lineage; the disclosure does not fix numeric values for them. This article describes that disclosed mechanism and does not assert any cryptographically signed time-to-live field, observation-class TTL maxima, or zeroed-contribution evaluator behavior beyond what the filing describes.
