Forecasting Engine Architecture

Mechanism

The forecasting engine architecture, defined in Chapter 4 of the cognition patent, decomposes the forecasting subsystem into a small number of declaratively coupled components, each of which performs a single architectural role and is replaceable independently of the others. The decomposition is structural rather than organizational: the boundary between components is enforced by typed interfaces declared in the policy reference, and no inter-component communication occurs outside those interfaces.

The input registry is the component that maintains the canonical set of inputs admissible to the forecasting subsystem. Each registered input carries a schema, a provenance descriptor, an admissibility tag, and a freshness predicate. Inputs that fall outside the registry, or whose freshness predicate has lapsed, are rejected at the engine boundary; the forecasting subsystem cannot operate on unregistered or stale inputs. The registry is itself a lineage-recorded artifact: additions, removals, and parameter changes are emitted as structured events.

The model registry is the component that maintains the set of forecasting models available for invocation. Each registered model carries a model identifier, a calibration tag, an input-binding declaration that specifies which registered inputs the model consumes, an output-binding declaration that specifies the structure of the model's emitted forecast, and a governance tag identifying the policy regime under which the model was admitted. Models are not invoked by name from outside the engine; they are invoked through the registry, which mediates input provisioning, calibration enforcement, and output channeling.

The output channels are the components that carry emitted forecasts to consumer subsystems. Each channel is typed by the structure of the forecasts it carries, and every forecast emitted on a channel includes a confidence value and a lineage handle. The confidence value is computed by the emitting model under the calibration in force at emission time; the lineage handle resolves to the full chain of inputs, model invocation parameters, and registry state that produced the forecast. Consumers cannot access the forecast value without simultaneously receiving its confidence and lineage; the channel structure prevents unbundled consumption.

The architecture supports modular replacement: a model in the model registry may be replaced by a successor model without altering the input registry, the output channels, or any consumer; an input source in the input registry may be replaced without altering models that consume it, provided the schema and freshness predicates are preserved; output channels may be added or retired without altering the input or model registries. Each replacement is itself a governance event recorded in the policy reference and lineage.

Operating Parameters

Each registered input is parameterized by its schema, its freshness predicate, its admissibility tag, and its retention horizon. The freshness predicate may be expressed as a maximum age, as a sequence-number invariant, or as a more complex temporal predicate; the engine evaluates the predicate at every model invocation that consumes the input. The retention horizon governs how long historical values of the input are preserved in the registry's queryable history, bounded below by minimum retention periods that protect lineage reconstructability.

Each registered model is parameterized by its calibration tag, its input bindings, its output bindings, its governance tag, and an invocation-policy descriptor specifying the conditions under which the model may be invoked. The invocation policy may specify rate limits, concurrency bounds, confidence-floor preconditions, and dependencies on other models. Calibration tags reference calibration audit records held in the policy reference; a model whose calibration audit is stale or absent is structurally prevented from emitting forecasts.

Each output channel is parameterized by its forecast schema, its consumer set, its delivery semantics, and the confidence and lineage attachment policy. The attachment policy is bounded structurally: confidence and lineage are mandatory and cannot be disabled by configuration. Delivery semantics may include push, pull, and broadcast variants, and each variant preserves the bundled-confidence-and-lineage property.

Per-component governance parameters specify the audit cadence, the change-control authority, and the compatibility envelope within which a component may evolve without triggering a system-wide governance review. Compatibility envelopes are enforced structurally: a model whose output schema falls outside its declared envelope cannot be admitted to the registry; an input whose schema falls outside its envelope cannot be admitted to the input registry.

Alternative Embodiments

In a first alternative embodiment, the model registry maintains an ensemble entry that aggregates plural underlying models under a declared aggregation rule. The ensemble is treated as a single registered model from the perspective of consumers; the ensemble's calibration tag references a composite calibration record that documents the calibration of each underlying model and the calibration of the aggregation rule.

In a second alternative embodiment, the input registry is partitioned into multiple sub-registries scoped to operational domains, and the model registry is correspondingly partitioned, so that models scoped to a domain may consume only inputs scoped to the same domain. Cross-domain forecasting is mediated by explicit bridging entries that are themselves registered and audited.

In a third alternative embodiment, the output channels include a speculative channel that carries forecasts marked as candidate rather than committed. Speculative-channel forecasts are consumed by the planning subsystem but are structurally prevented from being treated as verified inputs by other models; the channel typing enforces this separation.

In a fourth alternative embodiment, the engine supports hot-replacement of registered models in which a successor model runs in shadow alongside its predecessor for a configured comparison window before the predecessor is retired. The shadow output is recorded in lineage but not delivered to consumers; the transition from shadow to active is itself a governance event with its own audit record.

In a further alternative embodiment, the forecasting engine supports a federated configuration in which input registries and model registries are distributed across plural cooperating instances, with cross-instance invocation mediated by typed inter-registry interfaces that preserve the schema, freshness, and admissibility properties of the local registries. Federation does not weaken the bundled-confidence-and-lineage property: forecasts emitted by a remote model carry lineage handles that resolve across the federation boundary, and consumers cannot distinguish federated emissions from local emissions except by inspecting the lineage handle.

In a fifth alternative embodiment, the input registry supports synthesized inputs in which a registered entry is computed from other registered entries by a declared synthesis function. Synthesized inputs preserve the admissibility, freshness, and lineage properties of their constituents; cycles are structurally prohibited by registry validation.

Composition With Adjacent Mechanisms

The forecasting engine composes with the confidence-governance subsystem by emitting confidence values that participate in the agent's overall confidence aggregation, and by consuming confidence-floor signals that gate the invocation of models whose calibration is sensitive to operating conditions. When the agent is in a recovery phase, the engine restricts model invocation to those models whose governance tags admit operation under the active recovery tier.

The forecasting engine composes with the lineage subsystem by emitting registry events, model-invocation events, and forecast-emission events as first-class lineage artifacts. Every forecast that ever leaves the engine can be reconstructed deterministically from its lineage handle, including the input values consumed, the model and calibration used, and the registry state at the moment of emission.

The forecasting engine composes with the composite admissibility evaluator by treating forecasts as proposed inputs to downstream mutations: the evaluator consumes confidence and lineage from the output channels and applies its bounded-weight aggregation across forecasts and other evidence to determine admissibility.

Distinction From Prior Art

Prior art in forecasting subsystems typically employs monolithic architectures in which input handling, model invocation, and output delivery are implemented as a single integrated pipeline, or modular architectures whose modularity is organizational rather than structural — the boundaries are conventions enforced by code review rather than typed interfaces enforced by the architecture itself. Monolithic designs cannot be evolved without system-wide governance review; conventionally modular designs admit silent boundary violations that compromise the auditability of forecasts produced under those violations.

The forecasting engine architecture distinguishes itself by enforcing component boundaries through typed registry interfaces, by binding confidence and lineage to every forecast at the channel level, and by subjecting each component to independent governance with bounded compatibility envelopes. These properties are structural: they cannot be disabled by configuration, and any embodiment that disables them falls outside the disclosure.

Implementation Properties

The architecture preserves several structural invariants that follow from its decomposition. First, registry-mediated invocation: no model in the model registry can be invoked except through the registry's invocation interface, which performs input-binding resolution against the input registry, freshness predicate evaluation, calibration audit verification, and invocation-policy checks before the model is dispatched. Direct invocation pathways do not exist in the architecture; an implementation that admits them falls outside the disclosure.

Second, channel-bundled emission: the output channels are the only mechanism by which forecasts leave the engine, and the channel implementation forms the forecast value, the confidence value, and the lineage handle into a single emission record at the moment of dispatch. There is no implementation pathway by which a forecast can be emitted without its confidence and lineage; consumers receive the bundled record or no record at all. Third, governance scoping: each component carries a governance tag that defines its change-control authority and compatibility envelope. Replacement operations validate the successor against the envelope at registration time; out-of-envelope changes require a system-wide governance review whose record is itself a registry artifact.

Fourth, lineage-reconstructable forecasts: every emitted forecast can be deterministically reconstructed from its lineage handle, including the registry state at emission time. The implementation maintains registry snapshots indexed by lineage handle so that historical forecasts remain reconstructable even after registry contents have evolved. Fifth, structural cycle prohibition: the synthesis-input embodiment and the model-dependency embodiment are validated for acyclicity at registration time; a cycle in the synthesis or dependency graph is rejected at the registry boundary and cannot reach the running engine.

Disclosure Scope

The disclosure encompasses any forecasting subsystem decomposed into an input registry, a model registry, and output channels carrying mandatory confidence and lineage, in which each component is independently replaceable under per-component governance, regardless of the specific schemas employed, the specific aggregation or synthesis rules, or the specific delivery semantics of the output channels. Embodiments described herein are exemplary; the structural properties of registry-mediated invocation, bundled confidence and lineage, modular replaceability, and per-component governance define the scope of the claim.