Coherence Restoration Protocol Library

Mechanism

When the disruption-modeling subsystem diagnoses a disruption pattern, the diagnosis is presented to the protocol library as a structured query containing the pattern identifier, the severity profile, and the diagnostic confidence. The library matches the query against its indexed protocols, selecting the protocol whose entry criteria most closely match the diagnostic profile. Where multiple protocols match, the library applies a precedence ordering that prefers protocols with higher historical success rates against the matched pattern, with composition-compatible protocols selected where the disruption profile spans multiple pattern categories.

The selected protocol executes as a governed treatment plan. Each step in the protocol's intervention sequence is presented to the therapeutic-dosing primitive, which determines the dose intensity, the dose timing, and the response measurement window. Dosing is parameterized by the protocol step itself, by the agent's current state, and by the response trajectory observed in prior steps. After each step, the monitoring metrics defined by the protocol are evaluated against the protocol's expected response trajectory; deviations from the expected trajectory trigger one of three governance responses: in-protocol dose adjustment, in which the next step's dosing parameters are recalibrated; protocol substitution, in which the library selects an alternative protocol better matched to the observed trajectory; or escalation, in which restoration is referred to external supervisory intervention.

Exit criteria are evaluated after each step and continuously between steps. Successful restoration is declared when the monitoring metrics return to within the protocol's defined coherent-operation envelope and remain there across a stabilization window. Unsuccessful restoration may be declared if the monitoring metrics fail to converge within a defined treatment horizon, at which point the protocol terminates and the disruption is reclassified for re-diagnosis. Each protocol execution, whether successful or unsuccessful, is recorded in the protocol library's outcome history and contributes to the precedence ordering applied to future protocol selection.

Operating Parameters

Operating parameters of the restoration protocol library include the entry-criteria match function, the precedence ordering policy, the dose intensity bounds, the response measurement window, the stabilization window, the treatment horizon, and the escalation threshold. Entry criteria are expressed as structured predicates over the diagnostic profile, supporting both exact pattern matches and similarity-bounded matches against pattern combinations not previously catalogued. The precedence ordering policy combines historical success rate, diagnostic-confidence weighting, and protocol-composition compatibility; the policy is itself parameterized so that deployments may emphasize, for example, conservative protocol selection in safety-critical operational contexts.

Beyond the principal parameters, deployments configure secondary parameters governing protocol versioning, library indexing strategy, the policy under which novel disruption patterns admit provisional protocols, and the audit cadence under which historical protocol executions are reviewed for outcome consistency. Protocol versioning is enforced strictly: once a protocol is admitted to the production library, modifications produce a new version rather than mutating the existing version, so that historical executions remain interpretable against the protocol version under which they were performed. The library indexing strategy may be exact-match against pattern identifiers, similarity-bounded against pattern feature vectors, or hierarchical against a pattern taxonomy; the choice governs the breadth of disruption profiles that admit a stored protocol.

Dose intensity bounds are protocol-step-specific and are enforced by the therapeutic-dosing primitive. The bounds prevent corrective adjustments from exceeding magnitudes at which the adjustment itself would risk deepening the disruption. The response measurement window governs how much time elapses between dose application and response evaluation; the stabilization window governs how long monitoring metrics must remain within the coherent-operation envelope before successful restoration is declared; and the treatment horizon governs the maximum duration of a single protocol execution before escalation. The escalation threshold governs what constitutes a deviation severe enough to trigger external supervisory referral rather than in-protocol adjustment.

Alternative Embodiments

One embodiment expresses each protocol as a finite-state machine in which steps correspond to states and trajectory deviations correspond to state transitions, supporting compact specification of protocols whose step sequences depend on intermediate observations. A second embodiment expresses protocols as parameterized templates, with dose intensities, window durations, and step counts populated at execution time from the diagnostic profile; this embodiment supports rapid adaptation to novel disruption patterns by reuse of an existing template with adjusted parameters.

A third embodiment supports protocol composition at execution time: when a disruption profile spans multiple pattern categories, two or more protocols are interleaved, with the therapeutic-dosing primitive arbitrating between them to prevent dose interactions from exceeding combined intensity bounds. A fourth embodiment supports protocol learning, in which successful executions contribute to a learned protocol repository whose entries are validated against simulated disruptions before admission to the production library. A still further embodiment binds the protocol library to the agent's training-time curriculum, so that disruption patterns observed during training generate candidate protocols that are validated through the same evidence-based gating mechanisms that govern skill admissibility in the deployed agent.

Composition

The restoration protocol library composes with the disruption-modeling subsystem that produces diagnostic profiles, with the therapeutic-dosing primitive that governs corrective adjustment magnitude and cadence, with the monitoring infrastructure that produces the metrics evaluated against protocol trajectories, and with the supervisory escalation channel that receives restoration referrals when in-protocol adjustment is insufficient. Composition with therapeutic dosing is the core compositional relationship: every protocol step is mediated by the dosing primitive, and the protocols themselves do not encode raw corrective commands but dosing parameter sets. This composition prevents protocols from being applied as bare interventions and ensures that the magnitude and cadence governance enforced by the dosing primitive applies uniformly across the library.

Composition with the disruption-modeling subsystem provides the diagnostic input on which protocol selection depends; composition with the monitoring infrastructure provides the trajectory signal that governs in-protocol adjustment, substitution, and escalation; composition with the supervisory channel provides the failure path that prevents indefinite protocol execution against restoration-resistant disruptions.

The compositional relationship with the therapeutic-dosing primitive deserves further elaboration. The dosing primitive is not a generic rate-limiter; it maintains state across protocol steps, tracking the cumulative magnitude of corrective adjustments applied to the agent within a defined treatment window and enforcing aggregate intensity bounds in addition to per-step bounds. This stateful dosing prevents protocol step sequences that, while individually within step-level bounds, would in aggregate exceed the magnitude at which corrective adjustment is structurally safe. The dosing primitive also tracks dose-response correlations across protocol executions, contributing to the historical success-rate metric that informs precedence ordering at protocol selection time.

A further compositional relationship exists with the agent's coherence model. Successful restoration is defined not merely by the return of monitoring metrics to a coherent-operation envelope but by the agent's ability to resume the operational tasks that were in progress at the moment of disruption detection. The coherence model provides the predicate against which task-resumability is evaluated, and the protocol library defers exit-criterion satisfaction until the coherence model confirms task-resumability in addition to metric envelope return. This composition prevents premature declaration of successful restoration in cases where the agent's metrics have stabilized but its operational capability has not been restored.

Composition with the lineage retention substrate causes each protocol execution to be recorded as a structured event chained into the agent's operational history, supporting downstream audit of the disruption-and-restoration sequence. The structured event captures the diagnostic profile that triggered the protocol, the protocol identifier and version selected, the dose history applied, the trajectory observed, and the exit determination. This audit trail supports both engineering review of restoration outcomes and regulatory review where the operational context imposes such requirements.

Prior-Art Distinction

Conventional anomaly-recovery mechanisms in machine-learning systems either restart the affected component, fall back to a prior checkpoint, or invoke a bare corrective heuristic; they do not maintain a library of indexed restoration protocols, do not compose recovery with a dosing primitive, and do not support in-protocol adjustment or protocol substitution based on response trajectory. Reinforcement-learning safe-recovery approaches address state-space recovery without encoding the disruption-pattern-to-protocol indexing or the multi-step governed-trajectory structure. Medical-treatment-protocol analogies in software systems have addressed individual treatment steps but not the composition of an indexed protocol library with a dosing primitive and a governed escalation channel. The combination disclosed here is not present in the prior art.

Disclosure Scope

This article forms part of the disclosure of the Cognition Patent. The disclosure encompasses the indexed protocol library, the entry-criteria match function, the in-protocol adjustment, substitution, and escalation governance, the composition with the therapeutic-dosing primitive, and the alternative embodiments described above. The disclosure scope extends to all agent-restoration architectures in which structured intervention plans are indexed against diagnostic disruption profiles, executed as governed treatment plans under therapeutic-dosing mediation, and subject to trajectory-based in-protocol adjustment and escalation, regardless of the specific protocol-representation, dosing scheme, or escalation channel employed.