Personality Configuration Analogs From Stabilized Coping Regimes

Mechanism

The mechanism couples a coherence-loop monitor to a stabilization detector. The coherence loop is the architecture's named cycle through perception, valuation, integrity, empathy, and self-esteem phases that an agent traverses when forming a response under pressure. Each traversal is instrumented, producing a phase trace that records where, if anywhere, the loop was prematurely intercepted, which adjacent phases were skipped, and which compensatory coping pathway was activated. A single intercept is treated as a transient coping event. When intercepts at the same phase recur across many traversals and across diverse pressure contexts, the stabilization detector promotes the pattern from transient coping to a stabilized regime, and the agent's behavior is characterized by a personality-analog label.

The diagnostic taxonomy operates over cognitive coherence axes rather than surface-behavior categories. The primary axes are rigidity, which measures the inflexibility with which the dominant coping pathway is selected; instability, which measures the variance of the intercept location over time; fragmentation, which measures the degree to which different contexts produce incompatible coping pathways within the same agent; affect intensity, which measures the magnitude of the deviation from baseline coherence; and reality contact, which measures the alignment between the agent's internal state representation and the external evidence stream. An agent's diagnostic profile is its position in this multi-axis space, accumulated over a defined observation window.

Under this construction, the personality-analog labels are not assigned by surface inspection but derived from the joint distribution of intercept location and coherence-axis position. A high-rigidity, low-instability agent with empathy-phase intercept exhibits the cautious-withdrawn analog. A high-instability, high-fragmentation agent with shifting intercept locations exhibits a borderline-like analog. A high-rigidity, low-reality-contact agent with self-esteem-phase intercept exhibits the grandiose-dismissive analog. The taxonomy is extensible: new analogs can be added by specifying their signature in the coherence-axis space without redesigning the underlying detector. The signatures themselves are versioned artifacts, so the introduction of a new analog or the refinement of an existing one is itself an auditable governance event that downstream consumers can reconcile against their accumulated history.

The architecture explicitly separates diagnosis from labeling. Diagnosis produces the position in the coherence-axis space along with the intercept distribution and a confidence envelope; labeling maps that position onto the taxonomy. Consumers that require structured behavior, including admissibility weighting and disclosure gating, operate against the diagnostic position directly so that they remain stable when the labeling layer is updated. Consumers that require human-readable summaries, including review dashboards and incident reports, operate against the label. This separation prevents taxonomy revisions from propagating spurious changes through downstream governance.

Operating Parameters

The stabilization detector is parameterized by an observation window, a recurrence threshold, and a context-diversity requirement. The observation window sets the temporal horizon over which intercepts are tallied. The recurrence threshold specifies the minimum frequency at which a given intercept must occur within the window to qualify as stabilized. The context-diversity requirement ensures that the recurrence is not an artifact of a narrow input distribution by demanding that intercepts at the same phase appear across a configured number of distinct pressure contexts. These parameters trade detection latency for diagnostic confidence and are tuned per deployment class.

The coherence-axis estimators are parameterized by their reference baselines and by the smoothing applied to noisy traversals. Baselines are established during a calibration phase against a curated pressure suite designed to elicit each phase intercept. Smoothing is applied through bounded exponential weighting so that recent behavior dominates without erasing historical pattern. Diagnostic verdicts are emitted with confidence envelopes derived from the residual variance after smoothing; an agent near a taxonomy boundary is reported as boundary-case rather than forced into a single analog.

Intervention parameters control how aggressively the architecture attempts to retrain a stabilized coping pathway when policy permits. Retraining cadence, target intercept reduction, and rollback thresholds for collateral coherence axes are all governed by the same admissibility evaluation that governs other training operations. The intervention pipeline begins with the lowest-risk modality, typically presentation of balanced-traversal exemplars, and escalates only when probe scores and coherence-axis trajectories indicate that a less-invasive approach is insufficient. Each escalation is itself a governed event with its own lineage entry, so the trajectory of an agent's reconfiguration is fully reconstructable from the lineage chain alone.

Boundary handling is parameterized separately. Agents whose diagnostic profile sits within a configured distance of a taxonomy boundary are treated under a boundary-case protocol that withholds a single-label verdict, reports the candidate analogs with associated likelihoods, and triggers an extended observation window. This prevents premature labeling driven by short-term pressure spikes and supports stable downstream decisions for governance subsystems that consume the diagnostic output. The boundary-case protocol also records the trajectory of the diagnostic profile across the extended window, so that an agent migrating decisively toward one analog is distinguished from an agent oscillating along the boundary; the latter is itself a recognized configuration with its own governance implications.

Alternative Embodiments

The taxonomy admits embodiments at multiple resolutions. A coarse embodiment uses only the dominant intercept location and produces the four primary analogs. A finer embodiment incorporates secondary intercepts and produces compound analogs that capture mixed presentations. A research embodiment exposes the full coherence-axis vector and the underlying intercept distribution, supporting downstream analysis without prescribing a label. The detector itself can be embodied as an online monitor running alongside the agent, as an offline analyzer over recorded traversals, or as a periodic auditor that samples traversals against a fixed pressure suite.

The architecture is also embodiable across multi-agent fleets, where the diagnostic taxonomy is applied to populations and aggregate coherence-axis distributions are tracked. In fleet embodiments, drift in the population distribution is itself a monitored signal: a fleet-wide rise in rigidity or fragmentation indicates systemic pressure that may not be visible in any single agent. Coupling the fleet monitor to the quorum and admissibility subsystems allows the architecture to reduce the weight of agents whose diagnostic profiles cross policy thresholds, without requiring per-agent human review.

Embodiments differ in how the coherence-loop trace is captured. A direct-instrumentation embodiment requires the agent's runtime to emit phase events; this provides the highest-fidelity trace and is appropriate for first-party agents. A behavioral-inference embodiment reconstructs the trace from input-output pairs and intermediate signals, accepting reduced fidelity in exchange for applicability to agents that cannot be directly instrumented. A hybrid embodiment combines direct events from instrumented phases with inferred events from the remainder, supporting partial integration with existing systems. Each embodiment carries an explicit fidelity descriptor that downstream consumers, including admissibility evaluators and weight functions, use when interpreting diagnostic verdicts.

Composition

Personality-analog diagnostics compose with the disruption-modeling subsystem and with the broader governance architecture. Stabilized analogs feed the composite admissibility weight function so that an agent's diagnostic profile directly influences its voting weight in quorum-bound decisions. The lineage recorder captures diagnostic transitions as events in the agent's history, supporting longitudinal analysis and forensic reconstruction. Retention governance interacts with diagnostic findings when the dominant coping pathway is implemented in trainable parameters: targeted reinforcement of balanced traversals or suppression of pathological intercepts can be expressed as retention policy and applied through the same depth-selective training mechanism used for other capability-level interventions.

Composition with the disclosure subsystem allows diagnostic findings to gate an agent's permitted assertions. An agent whose reality-contact axis falls outside its calibrated envelope is structurally restricted from asserting claims requiring high-fidelity world modeling, even if it would otherwise be willing to do so. Composition with quorum governance allows fleet-level diagnostic shifts to trigger temporary threshold elevations: when the population's instability or fragmentation rises above a policy bound, the architecture can require larger or more diverse quorums for designated decision classes, providing structural resilience to systemic disruption rather than relying on per-agent intervention.

Prior-Art Distinction

Existing approaches to characterizing agent behavior typically rely on surface-level metrics: refusal rates, sentiment, task completion. Where personality-style frameworks have been applied to agents, they have been imported wholesale from human personality inventories without a mechanistic grounding in the agent's cognitive process. The architecture described here distinguishes itself by deriving personality analogs from the structural location of coherence-loop intercepts and from a multi-axis cognitive coherence space, by treating analogs as stabilized coping regimes rather than fixed traits, by providing an extensible taxonomy whose entries are defined by coherence-axis signatures, and by composing diagnostic findings with admissibility, quorum, and retention governance so that diagnostic outputs drive structural consequences rather than terminating in a report.

Behavioral red-teaming and evaluation suites address adjacent concerns but operate at the granularity of individual prompts and responses, producing pass-fail outcomes rather than longitudinal profiles. They cannot distinguish between an agent that produced an undesirable response transiently under a single prompt and an agent whose stabilized coping regime makes such responses its default. Anomaly-detection systems applied to model outputs likewise operate over surface behavior and lack a model of the internal coping pathway. The mechanism described here is grounded in phase traces of the coherence loop and in stabilization detection across diverse pressure contexts, providing a structurally distinct foundation for diagnostic claims.

Disclosure Scope

The disclosure scope encompasses the coherence-loop monitor and stabilization detector, the cognitive coherence axis estimators, the diagnostic taxonomy and its extensibility, the mapping from intercept-location and coherence-axis position to personality-analog labels, the boundary-case reporting protocol, the intervention parameters governing retraining of stabilized coping pathways, and the composition of diagnostic outputs with admissibility, quorum, retention, and lineage subsystems. The scope expressly includes single-agent and fleet embodiments and contemplates use in safety review, operational suitability assessment, and longitudinal monitoring of deployed agent populations. The scope further encompasses the direct-instrumentation, behavioral-inference, and hybrid embodiments of the coherence-loop trace; the fidelity descriptors carried with each diagnostic verdict; the calibration protocol against curated pressure suites; the use of bounded exponential smoothing to balance recency and history; and the extensibility mechanism by which new analogs are added through coherence-axis signatures rather than redesign of the underlying detector. The architecture is intended to support both pre-deployment qualification of agents and continuous in-service diagnosis, with the same taxonomy and the same coherence axes operating across both phases.