Forecast-Uncertainty-Driven Sensor Solicitation

Mechanism

The forecasting engine maintains a continuously updated estimate of uncertainty for each ongoing forecast. Uncertainty here is not a single scalar; it is a structured object that may include posterior variance, ensemble disagreement, model-class divergence, time-to-stale, and credentialed-input freshness. Each component is stamped with the credential that authorized its computation, so a downstream consumer can evaluate not only the magnitude of the uncertainty but the authority basis on which the magnitude was computed. The structured object is itself an observation under the same taxonomy that governs sensor reports and forecast products, which means it is addressable, supersedable, and admissibility-evaluable in identical fashion.

When any credentialed component of the uncertainty object crosses a published threshold for a specific spatial-temporal region, the engine constructs a solicitation observation. The solicitation is itself a credentialed observation in the same observation taxonomy as sensor reports and forecast products — it carries the issuing engine's identity, the region of interest, the uncertainty components driving the solicitation, the freshness window in which a response is admissible, the policy class against which responses must be evaluable, and the rate-limit and quorum parameters that govern aggregate response. Because the solicitation is structurally identical to any other credentialed observation, it requires no protocol surface beyond what the mesh already provides; receivers consume it through their normal admissibility pipeline.

The solicitation propagates through the mesh. Mobile units (vehicles, drones, robots) within reachable distance may divert toward the region. Fixed sentinels in or near the region may increase their sensing rate or expand their bandwidth allocation. Directed sensors — steerable cameras, scannable radars, controllable acoustic arrays — may retask their pointing. Peer forecasting engines may run their own models against the region and emit comparison forecasts. Each response is itself a credentialed observation gated by the responding unit's admissibility evaluation: mission priority, energy budget, capability constraint, authority compatibility. No responder is compelled; each evaluates the solicitation against its own sovereign admissibility framework and either responds, declines, or partially complies under explicit credentialed acknowledgment of the partial compliance.

Responses flow back as ordinary credentialed observations consumed by the originating engine. The engine recomputes its uncertainty object, and the loop terminates when the uncertainty drops below the release threshold or when the freshness window expires. Termination is itself a credentialed event: the engine emits a solicitation-closure observation that allows responders to release diverted capacity for other work, and that closure observation is auditable evidence that the loop closed deterministically rather than expiring silently. If the loop fails to converge — responses do not reduce uncertainty, or no admissible responder is reachable — the engine emits an explicit unresolved-solicitation observation under its credentials, and downstream consumers gate their actions on that evidence rather than acting on the unresolved forecast.

The closed-loop structure therefore has four distinguishable operations, each credentialed and each observable: uncertainty assessment, solicitation issuance, response composition, and closure. None is a procedural call into a coordinator; each is the publication of a credentialed observation against the published policy class. The architectural consequence is that the loop is replayable from its observation log alone, which is what makes regulatory acceptance feasible and what allows operators of multiple authorities to participate without surrendering sovereignty.

Operating Parameters

Four parameter classes govern the loop. The threshold class specifies which uncertainty components, at which magnitudes, under which credentials, may trigger a solicitation; thresholds are policy-bound and are themselves observable, so a regulator or operator can audit the trigger configuration without inspecting source code. The scope class constrains the spatial-temporal extent of the solicitation, the maximum number of responders that may be retasked simultaneously, and the maximum aggregate cost (energy, bandwidth, mission disruption) that responders may incur in aggregate across the loop. The scope class is what makes the solicitation a bounded request rather than an unbounded broadcast, and it is what allows operators to publish operating envelopes that bind every solicitation regardless of which engine issued it.

The rate-limit class bounds the engine's solicitation production. A single engine cannot saturate the mesh with solicitations regardless of its internal uncertainty: the rate-limit policy specifies maximum solicitations per region per time window, maximum concurrent open solicitations per engine, and the back-off behavior when responses fail to reduce uncertainty. Rate-limiting prevents a malfunctioning forecaster from monopolizing collective observation capacity, prevents adversarial behavior in which a compromised engine would attempt to direct observation traffic, and provides the structural basis for graceful degradation when the mesh is saturated by simultaneous unrelated solicitations from multiple engines. The back-off behavior is itself observable, so a regulator can audit whether engines under their jurisdiction are exhibiting good citizenship under load.

The quorum class specifies how many credentialed responses, from how many distinct authority sources, are required before the engine treats the resulting reduced uncertainty as authoritative. A solicitation answered by only a single responder of a single authority class produces a reduced-uncertainty estimate stamped accordingly; an estimate from a cross-source quorum is stamped with a stronger authority basis. Downstream consumers of the forecast read the authority stamp and gate their own actions on it. Quorum is what prevents a single rogue responder from collapsing the engine's uncertainty estimate, and it is what makes cross-authority composition safe: the quorum policy can require cross-authority responses for high-stakes downstream actions, while permitting same-authority quorum for routine refinement.

The fourth class is the closure class, which specifies the conditions under which the engine emits the closure observation that releases responder capacity. Closure may be triggered by uncertainty falling below a release threshold (which is published separately from the trigger threshold and is typically lower, providing hysteresis), by expiration of the freshness window, by accumulation of sufficient quorum-stamped responses, or by an explicit operator-credentialed override. The closure observation is the audit anchor for the loop and is the evidence that releases responders to other work; without the closure event, responders remain committed under the solicitation's terms until the freshness window expires.

Alternative Embodiments

The primitive composes across application domains without modification to the loop. In autonomy fleets, the engine forecasts traffic, weather, occlusion, and regional demand; uncertainty solicitation retasks vehicle-mounted sensors and roadside infrastructure to reduce uncertainty before downstream planning consumes the forecast. The vehicles are sovereign responders — each evaluates the solicitation against its own mission priority, energy budget, and authority compatibility — and the requesting engine does not negotiate with any individual vehicle. In smart-grid forecasting, the engine forecasts load and generation; uncertainty solicitation retasks utility-side telemetry and customer-side smart meters to reduce uncertainty before dispatch. The customer-side meters respond under their own credentialed admissibility, which respects privacy and metering-authority constraints without requiring the engine to be aware of them.

In defense ISR, the engine forecasts threat posture; uncertainty solicitation retasks ISR platforms and allied-force sensors under coalition admissibility rules. Coalition members respond under their own coalition credentials, and quorum policy enforces cross-coalition composition for high-stakes downstream actions. In weather-services embodiments, commercial mobile-observation contributors (rideshare fleets, package-delivery fleets, agricultural fleets) act as responders under credentialed integration; their participation is governance-bound by the published threshold and rate-limit policy, and their contributions are stamped with their authority class so downstream consumers can evaluate the authority basis of the resulting forecast. A closed-fleet embodiment treats only same-operator units as responders; the primitive is indifferent to which composition is in force because the loop, the credentialed solicitation observation, the rate-limit and quorum parameters, and the closure event are common across all of them.

Embodiments differ in which contributor classes are reachable, which authority classes are recognized, and which policy classes are published — but the loop is invariant. An emergency-response embodiment may publish an emergency policy class with relaxed scope and rate-limit parameters during declared incidents; a routine-operations policy class binds the same engine the rest of the time. The transition between policy classes is itself a credentialed observation, so the engine's behavior is auditable across policy regimes.

Composition

Uncertainty-driven solicitation composes with the broader cognition-patent architecture. The forecasting engine does not need to know which contributors will respond; it constructs a solicitation observation under its own credentials and publishes it. The mesh's credentialed-observation taxonomy ensures that responders evaluate the solicitation through the same admissibility framework they apply to all other governance-bound work. The capability-awareness layer ensures that responders advertise only capabilities they can credentialedly perform; the spatial-mesh layer ensures that solicitation, response, and closure events are addressable in the same spatial-temporal substrate that the forecast itself operates on. The architectural consequence is that adding a new responder class — a new sensor type, a new platform class, a new authority — requires no modification to the forecasting engine; the responder enters the mesh, advertises its capabilities, and begins consuming solicitations through the existing pipeline.

Crucially, the responding unit is not subordinated to the requesting engine. Each responder's admissibility evaluation is sovereign: mission priority, capability constraint, and authority compatibility are evaluated locally. A responder that declines a solicitation does so under its own credentials, and the declination is itself observable, so the requesting engine can adapt its strategy without negotiating with the responder. The sovereign admissibility model is what allows the primitive to operate across operators who would not delegate dispatching authority to a shared coordinator, and is what allows responders to participate in solicitations from multiple engines simultaneously without conflict — each solicitation enters the responder's admissibility framework and is composed with the others under the responder's published policy.

The primitive also composes with the disclosure's quorum-evaluation and authority-stamping layers. A reduced-uncertainty estimate produced by quorum-stamped responses is a stronger evidentiary basis for downstream actions than an estimate produced by single-source response, and the stamping is structurally evaluable rather than empirically inferred. Downstream planners gate their actions on the stamp, which closes the loop between active perception and downstream decision-making at the architectural layer rather than within an integration engineer's discretion.

Prior-Art Distinction

Active perception (Bajcsy 1988 and the subsequent next-best-view literature, including Connolly 1985, Pito 1999, Chen and Li 2005, and the more recent learning-based active-perception work) operates within a single robot's sensor budget: the robot allocates its own sensors to reduce its own forecast uncertainty. The pattern is mature for individual robots and is incorporated by reference where applicable. It does not compose to fleet scale because it lacks credentialed cross-unit solicitation, lacks rate-limit and quorum governance, and lacks the structural admissibility evaluation by which a sovereign responder may decline. Extending single-robot active perception to a fleet by adding a coordinator reproduces a centralized chokepoint and does not address the cross-authority case.

Multi-robot coordination literature (auction-based task allocation per Gerkey and Mataric, market-based multi-robot systems per Dias et al., consensus-based bundle algorithms per Choi et al.) provides cross-unit allocation but presupposes a shared utility function and a shared authority basis. The disclosed primitive does not require shared utility: each responder evaluates against its own admissibility framework, and the requesting engine consumes responses through its own credentialed-observation pipeline. The two need not share an objective. This distinction matters because in cross-operator deployments — coalition defense, multi-jurisdiction transportation, multi-utility grid — there is no shared utility function to optimize, and any architecture that presupposes one is operationally inadmissible.

Centralized tasking systems (ISR collection management, fleet dispatch, ATC) provide governance but at the cost of a centralized chokepoint. The disclosed primitive replaces centralized tasking with credentialed solicitation: governance is enforced by the policy-bound threshold, rate-limit, and quorum parameters rather than by a single coordinator. The architectural change is what allows the primitive to scale to multi-authority deployments where no single coordinator is acceptable. Where centralized tasking exists in an embodiment, it can issue solicitations under its credentials as one among many issuers; its authority is not architecturally privileged.

Information-theoretic active sensing (mutual-information maximization, Bayesian experimental design, Krause and Guestrin's submodular-sensing work) provides the mathematical apparatus for choosing what to observe in order to reduce uncertainty. The disclosed primitive incorporates that apparatus by reference inside the engine's threshold and uncertainty-component computation; the contribution of the disclosure is not the mathematical apparatus but the architectural layer at which the apparatus is exposed as a credentialed cross-authority closed loop.

Disclosure Scope

The disclosure covers the credentialed solicitation observation, the threshold/scope/rate-limit/quorum parameter classes, the cross-unit response composition, and the closure event. It covers embodiments across autonomy, smart-grid, weather-services, defense-ISR, and emergency-response domains. It covers compositions in which responders are same-operator and compositions in which responders are cross-operator under coalition admissibility. It covers the structured uncertainty object with credential-stamped components, and it covers the authority-stamping of reduced-uncertainty estimates by quorum class. It explicitly disclaims reliance on a shared utility function across responders; admissibility is sovereign.

The disclosure also covers the explicit unresolved-solicitation observation as the structural artifact that gates downstream consumers when a loop fails to converge, and it covers hysteresis between trigger and release thresholds as the mechanism that prevents oscillation in steady-state operation. It covers the policy-class transition mechanism by which embodiments shift between operating regimes (routine, emergency, coalition) under credentialed transitions that are themselves observable.

The disclosure is positioned at the architectural layer where fleet-scale active perception has been operating without structural support. It is the layer at which forecasting and observation become a closed loop without becoming a centralized chokepoint, and at which collective observation capacity becomes a governance-bound resource rather than an ad-hoc per-unit allocation. The disclosure's contribution is the structural primitive — credentialed solicitation, sovereign admissibility, parameterized governance, observable closure — not the mathematical apparatus of uncertainty quantification, which is incorporated by reference where applicable.