Temporal Anchoring and Lifecycle Management

Mechanism

The mesh-time substrate is a distributed time service in which multiple independent witnesses agree on monotonic time stamps via a deterministic agreement protocol. Each time stamp issued by the substrate is a structured anchor: a tuple binding a wallclock claim, a logical sequence number, and a cryptographic signature derived from the witnesses' agreement. The substrate guarantees that an anchor is verifiable against the witness set without contacting the witnesses again, and that two anchors can be ordered against one another using the logical sequence even if their wallclock claims disagree within a known tolerance. This substrate is the ground truth against which the forecasting engine binds its outputs.

When the engine generates a forecast branch, it acquires an anchor set composed of at least three elements: an origin anchor recording when the branch was created, an evidence anchor for each piece of observational input that supports the branch, and a horizon anchor specifying the mesh-time interval over which the forecast claims validity. The anchor set is bound to the branch's lineage record at creation and is updated only by appending; the engine never silently rewrites an anchor. As a branch evolves through evaluation, dormancy, or aggregation, additional anchors are appended to record significant state transitions, but the original anchor set remains in place as a tamper-evident record of provenance.

Cross-anchor consistency checks run at three points in the lifecycle. At creation, the engine verifies that the origin anchor strictly succeeds all evidence anchors in mesh-time ordering, ruling out forecasts that claim to depend on observations from the future. At evaluation, the engine verifies that the branch's horizon anchor has not yet been crossed by current mesh time and that no evidence anchor has been repudiated by the substrate; a repudiated anchor is one the witness set has retracted, for example because a witness was found to be compromised. At commitment, the engine verifies that all anchors remain valid and that the branch's logical sequence is consistent with the rest of the executive summary it participates in. Any check failure invalidates the branch and triggers a transitive invalidation across all branches whose lineage depends on the failed branch's outputs.

Tampering is detected structurally rather than statistically. Because anchors are signed by the witness set, any modification to a stored anchor breaks its signature and is detected on the next verification. Because the engine retains the full anchor set on the lineage record, no later state can claim a different provenance than was originally established. And because invalidation cascades transitively, an attacker who compromises a single anchor cannot quietly prune the cascade; the structural dependency graph forces every dependent forecast into an invalidated state until the underlying anchor is replaced or the dependent forecasts are explicitly recomputed against fresh anchors.

Operating Parameters

A deployment is governed by several declarative parameters. The witness set size and quorum threshold determine how many independent witnesses must concur for an anchor to be accepted, balancing tamper resistance against availability. The anchor freshness window specifies how recent an anchor must be to count as valid evidence, preventing very old observations from re-entering the active forecast space without explicit refresh. The clock tolerance specifies the maximum permitted disagreement among witness wallclock claims before an anchor is rejected as inconsistent. The horizon policy defines how horizon anchors are computed and may be domain-specific, for example longer for strategic forecasts and shorter for tactical ones.

Additional parameters govern audit and observability. The anchor manifest schema specifies which fields of an anchor are exposed to downstream consumers and which remain internal to the engine; this controls the granularity at which a downstream consumer can verify provenance without exposing substrate-internal details. The repudiation channel specifies how the witness set communicates retraction events to the engine, including subscription, polling, and pull-on-verify modes; the chosen channel determines the maximum latency between a repudiation event and the corresponding invalidation cascade. Two further parameters govern invalidation behavior. The cascade depth bound limits how far transitive invalidation will propagate in a single cycle, with overflow handled by deferring further propagation to the next cycle and recording the deferral as an audit event. The replacement policy specifies whether an invalidated branch is archived, queued for re-anchoring against fresh evidence, or simply removed; the choice is recorded and is itself a parameter under audit.

Alternative Embodiments

Temporal anchoring admits embodiments that vary the underlying substrate without changing the structural contract. A centralized embodiment uses a single trusted timekeeper whose signatures stand for the witness quorum; this is appropriate for closed deployments. A federated embodiment uses a fixed witness set whose membership is governed by a separate consensus protocol. A blockchain-anchored embodiment binds anchors to entries in an external immutable ledger, which provides tamper evidence even if all in-mesh witnesses are compromised. A hybrid embodiment binds short-horizon forecasts to fast in-mesh anchors and long-horizon forecasts to slower but more strongly authenticated external anchors. In each embodiment, the engine performs the same cross-anchor checks, the same transitive invalidation, and the same lineage retention; only the trust root and latency profile differ.

Further embodiments address operational and forensic considerations. A retrospective-replay embodiment retains enough anchor metadata that a forecast can be replayed against the historical state of the witness set, allowing an investigator to determine whether an invalidation was caused by witness compromise, by clock drift, or by an underlying logical inconsistency in the forecast itself. A staged-commitment embodiment introduces an intermediate state between forecast generation and downstream commitment in which anchors are revalidated against a fresh witness sample; this is useful when the time between forecast generation and action is long enough that an anchor that was valid at generation may have been repudiated in the interim. A multi-substrate embodiment requires that high-stakes forecasts be anchored against two independent substrates and rejects the forecast if the substrates' orderings disagree beyond tolerance, providing defense-in-depth against substrate-specific attacks.

A delegated-trust embodiment allows a peer agent to vouch for a remote anchor by signing it with its own credential, with the engine then performing trust composition between the peer's credential and its own root of trust; this is useful in cross-organizational mesh deployments where direct witness access is impractical. A rate-limited embodiment caps the rate at which anchors may be acquired per branch to prevent denial-of-service attacks against the substrate by runaway forecast generation. Across all embodiments, the structural contract is preserved: anchors are first-class lineage elements, cross-anchor consistency is checked at well-defined lifecycle points, repudiation propagates transitively to dependent forecasts, and every anchor-related event is recorded in the same monotonic audit lineage as the forecasts the anchors govern.

Composition with Other Cognition Mechanisms

A further compositional consideration is the interaction between anchoring and rate-limited downstream channels. When an anchor repudiation triggers a large transitive invalidation, the resulting cascade may produce a burst of state changes that downstream consumers must absorb. The engine accordingly exposes the cascade depth bound and the deferral mechanism described earlier as composition-aware controls, allowing operators to tune the maximum impulse a single repudiation may inject into the downstream pipeline without sacrificing the eventual completeness of the invalidation. Temporal anchoring composes with branch dormancy by requiring anchor revalidation on revival; a dormant branch whose anchors have been repudiated is archived rather than rehydrated, preventing stale forecasts from re-entering active processing through the back door. It composes with executive aggregation by carrying anchor sets through alignment and arbitration; a summary node inherits the union of its contributing anchors, and any repudiation of a contributing anchor invalidates the summary node and triggers re-aggregation. It composes with the planning-graph containment boundary by ensuring that no branch can cross from forecasting state into committed action without first passing the anchor verification gate. The result is a forecasting engine in which time is not an ambient assumption but an explicitly verified component of every commitment, and in which tampering with time is structurally indistinguishable from invalidating the forecasts that depend on it.

Distinction from Prior Art

Conventional forecasting and planning systems treat time as a property of the data, not as an authenticated substrate. Time-stamped records may be signed for integrity, but the time stamp itself is rarely verified against an independent witness set, and dependent forecasts are rarely invalidated transitively when an upstream time stamp is found to be wrong. Distributed time services such as TrueTime provide bounded clock disagreement but do not bind their outputs into the lineage of dependent computations. Tamper-evident logs preserve history but operate on flat event streams rather than on graph-structured forecasts with transitive dependencies. Temporal anchoring is distinct in three respects: it treats anchors as first-class structural elements of every forecast, it propagates invalidation through the dependency graph rather than treating it as a per-record concern, and it makes time tampering and forecast tampering structurally equivalent failure modes that any audit can detect.

Disclosure Scope

This disclosure covers any forecasting subsystem in which forecasts are bound to verifiable time anchors drawn from a witness-backed substrate; in which cross-anchor consistency checks run at creation, evaluation, and commitment; in which anchor repudiation triggers transitive invalidation of dependent forecasts; and in which the anchor set of every forecast is retained as part of an immutable lineage record. The mechanism is applicable across deployment domains including autonomous vehicles, companion agents, therapeutic systems, and enterprise planning, and is not limited to any particular witness protocol, signature scheme, or anchor representation.

The disclosure further encompasses systems in which anchor verification is performed against the witness set's published state at the time of verification rather than against a cached witness state, systems in which the cascade of transitive invalidation is itself a recorded artifact subject to audit, and systems in which the choice of witness substrate, freshness window, and replacement policy is captured in a policy reference whose revision history is retained alongside the anchored forecasts. It encompasses deployments in which time itself is a contested resource, including domains where the integrity of regulatory time stamps is a compliance requirement and where the ability to demonstrate that no committed action was grounded in an unverified time claim is itself a material property of the system.