P239 — AIEP — Reasoning Strategy Lifecycle Management Engine

Applicant: Neil Grassby Classification: Patent Application — Confidential Priority: Claims priority from GB2519711.2 filed 20 November 2025 Architecture Layer: AIEP Phase 2 Support Layer

Framework Context

[0001] This specification operates within an AIEP environment as defined in GB2519711.2 and GB2519798.9. The present specification defines a system for managing the lifecycle of reasoning strategies across creation, evaluation, retention, refinement, and deprecation.

Field of the Invention

[0002] The present invention relates to reasoning strategy lifecycle management for meta-cognitive AI architectures.

Background

[0003] AIEP systems employ multiple reasoning strategies — evidence integration patterns, causal chain construction methods, counterfactual exploration approaches — that may be more or less effective depending on goal type, evidence quality, and world state complexity. Without lifecycle management, effective strategies may be lost through session termination and ineffective strategies may persist, degrading reasoning quality over time.

Summary of the Invention

[0004] The invention provides a Reasoning Strategy Lifecycle Management Engine (RSLME) that maintains a persistent strategy registry in the Long-Term Reasoning Memory Engine (P208). For each registered strategy, the RSLME tracks: usage history; quality scores from the Meta-Reasoning Quality Evaluation Engine (P214); goal type applicability; and version lineage.

[0005] New strategies are proposed by the system or operator, undergo an evaluation period, and are promoted to ACTIVE status upon meeting quality thresholds. Active strategies failing quality evaluation are moved to PROBATION and eventually DEPRECATED if quality does not recover.

ASCII Architecture

Strategy Proposal (System / Operator)
         |
         v
+-------------------------------------------+
| Reasoning Strategy Lifecycle Management   |
|   Engine (RSLME)                          |
|                                           |
|  Strategy Registry (LTM, P208)           |
|  Evaluation Period: track quality (P214) |
|  State machine: PROBATIONARY → ACTIVE    |
|                  ACTIVE → PROBATION      |
|                  PROBATION → DEPRECATED  |
+-------------------+-----------------------+
                    |
                    v
  Active Strategy Registry
  → Strategy selection in reasoning sessions

Detailed Description

[0006] Strategy Registry. The strategy registry is persisted in the Long-Term Reasoning Memory Engine (P208). Each entry records: strategy identifier, version, description, applicability conditions, quality score history, current lifecycle state, and usage count.

[0007] Evaluation Period. Newly proposed strategies enter PROBATIONARY state. During this period they are applied to a fraction of eligible reasoning sessions and their quality scores tracked. A minimum evaluation period of N sessions is required before promotion.

[0008] Quality-Based State Transitions. After the evaluation period: strategies with quality score above the promotion threshold are promoted to ACTIVE; strategies below the threshold remain PROBATIONARY for an extended period; strategies that remain below threshold after the extended period are DEPRECATED.

[0009] Active Strategy Monitoring. Active strategies remain in quality monitoring. If rolling average quality falls below the demotion threshold, the strategy is moved to PROBATION. If it recovers within the recovery window, it returns to ACTIVE; otherwise it is DEPRECATED.

[0010] Strategy Versioning. Refined strategies are stored as new versions, maintaining lineage links to parent versions. This allows quality trends to be tracked across lineages.

Technical Effect

[0011] The invention provides evidence-grounded, governed lifecycle management for AI reasoning strategies, ensuring that only strategies with demonstrated quality records are actively deployed. By requiring strategies to pass a probationary quality evaluation period before promotion to ACTIVE status, the engine prevents untested strategies from affecting production reasoning sessions. By continuously monitoring active strategy quality and demoting underperforming strategies to PROBATION, the engine provides adaptive self-improvement without uncontrolled strategy proliferation. By maintaining version lineage across refinements, the engine enables quality trend analysis across strategy evolution chains.

Claims

1. A computer-implemented method for reasoning strategy lifecycle management, the method comprising: (a) registering new strategies in CANDIDATE state and transitioning them to PROBATIONARY for evaluation over a policy-defined period; (b) evaluating probationary strategies using quality scores from the Meta-Reasoning Quality Evaluation Engine, promoting strategies above the promotion threshold to ACTIVE and extending the probationary period for strategies below it; (c) deprecating strategies that remain below threshold after the extended probationary period; (d) continuously monitoring active strategy rolling average quality, demoting strategies below the demotion threshold to PROBATION; and (e) maintaining version lineage links when strategies are refined, storing refinements as new versions linked to their parent version.

2. The method of claim 1, wherein strategy lifecycle state is persisted in the Long-Term Reasoning Memory Engine (P208), ensuring lifecycle continuity across system restarts.

3. The method of claim 1, wherein quality evaluations used for lifecycle decisions are admitted to the evidence ledger as strategy quality artefacts citing the strategy version and evaluation session.

4. The method of claim 1, wherein deprecated strategies are retained in the strategy archive and not deleted, preserving access for historical analysis and potential reactivation.

5. The method of claim 1, wherein quality trend analysis over version lineage enables identification of strategy families improving or degrading across refinement generations.

6. A Reasoning Strategy Lifecycle Management Engine comprising: one or more processors; memory storing a strategy registry, quality evaluation record index, and version lineage graph; wherein the processors are configured to execute the method of claim 1.

7. A non-transitory computer-readable medium storing instructions that, when executed by a processor, implement the method of claim 1.

Abstract

A reasoning strategy lifecycle management engine for evidence-bound artificial intelligence governs strategy progression through CANDIDATE, PROBATIONARY, ACTIVE, PROBATION, and DEPRECATED states based on quality scores from the Meta-Reasoning Quality Evaluation Engine. Active strategies are continuously monitored and demoted on quality degradation. Strategy version lineage is maintained across refinements enabling quality trend analysis. All lifecycle transitions are recorded in the AIEP evidence ledger.