Mechanism
Valence stabilization is one stage in the affective state update pipeline that governs how the agent's named control fields evolve over time. Each named control field in the affective modulation layer, such as uncertainty sensitivity, ambiguity tolerance, novelty appetite, persistence under partial failure, escalation under time pressure, risk sensitivity, and cooperation disposition, carries a current magnitude, a decay rate, a policy-defined ceiling and floor, and a timestamp of its most recent update. Stabilization is the mechanism that prevents these fields from entering oscillatory behavior, in which a field alternates rapidly between elevated and suppressed values in response to noisy environmental inputs or rapid alternation between success and failure conditions.
The stabilization stage sits within a defined sequence. Structured observations feed an update function, whose output is bounded by policy, then shaped by a decay curve, then processed for hysteresis, and then passed through entropy-governed stabilization before the result is recorded in the agent's lineage. Stabilization is therefore not a controller bolted onto the affective state; it is a step in the same deterministic update path that produces every affective mutation, and its effect is expressed through the same decay machinery that governs ordinary field relaxation.
Emotional Decay Curves
Each named control field is governed by an emotional decay curve that determines how the field value returns toward its baseline in the absence of reinforcing stimuli. The decay curve is a deterministic function of the time elapsed since the most recent update, the magnitude of the current deviation from baseline, and the decay parameters specified by the agent's policy configuration. In an embodiment, the decay is exponential with a configurable time constant: the field value at a given time after the most recent reinforcing update equals the policy-defined resting value plus the post-update deviation scaled by an exponential term in the elapsed time divided by the decay time constant.
Different named control fields may carry different decay time constants, reflecting the principle that some modulation dimensions are more persistent than others. The specification gives the example that uncertainty sensitivity may decay rapidly, because epistemic conditions change frequently, while persistence under partial failure may decay slowly, because learned persistence reflects deeper accumulated experience. The decay time constant is the quantity that the stabilization mechanism acts upon.
Semantic Hysteresis
The affective modulation layer exhibits semantic hysteresis, a property whereby the agent's current affective state depends not only on the current structured observations but also on the trajectory of prior states. Hysteresis is implemented through asymmetric update rules: the rate at which a named control field increases in response to a triggering observation may differ from the rate at which it decreases when the triggering condition is removed.
In an embodiment, negative valence updates, that is, updates driven by failure, uncertainty, or threat, apply at a higher rate than positive valence updates driven by success or stability. This asymmetry reflects the architectural principle that an agent should respond more rapidly to deteriorating conditions than it recovers from them, producing a built-in caution bias. Hysteresis precedes stabilization in the update pipeline, so the trajectory-dependent behavior is already established before the entropy-governed stage examines the recent update history.
Entropy-Governed Valence Stabilization
Entropy-governed valence stabilization is applied to prevent oscillatory affective behavior. The mechanism monitors the frequency and direction of recent updates to each named control field. When a field exhibits rapid alternation between elevated and suppressed values, the stabilization mechanism progressively increases the effective decay time constant for that field, which damps the oscillation by causing the field to relax more slowly and resist the rapid back-and-forth that the noisy input would otherwise induce.
The stabilization threshold and the damping factor are policy-configurable. By acting on the decay time constant rather than introducing a separate corrective signal, the mechanism keeps stabilization inside the same deterministic decay model that governs all field relaxation. The purpose is to prevent affective instability that could arise from noisy environmental inputs or from rapid alternation between success and failure conditions, so that the agent's modulation state remains usable rather than thrashing between extremes.
Determinism and Policy Bounds
Stabilization operates within the deterministic, policy-bounded discipline that governs every affective update. Given the same agent state, the same environmental inputs, and the same policy configuration, the affective update function produces the same output, so the stabilization behavior is itself reproducible and auditable. The decay parameters that stabilization adjusts are subject to decay governance: policy constraints specify minimum and maximum decay rates and whether decay is permitted to proceed below a field's baseline value, which prevents adversarial suppression of affective response through artificially accelerated decay.
Because the effective decay time constant that stabilization raises is bounded by these policy constraints, the damping cannot be driven to an extreme that would freeze a field permanently, nor can it be evaded by an input pattern that pushes the constant outside its admissible range. The clamping and validation stages that bound ordinary updates, including range bounds and rate limits, continue to apply to every field value the stabilized pipeline produces.
Relation to Volatility Quarantine
Entropy-governed stabilization is the field-level response to oscillation. The specification also describes a distinct, agent-level response for the case where stabilization is insufficient. A volatility detector computes a composite volatility metric from the recent update history of all named control fields, and when that metric exceeds a quarantine threshold the agent is routed to an emotional quarantine state with reduced operational scope. Release from quarantine occurs when the metric falls below a separate recovery threshold set below the quarantine threshold, which provides hysteresis and prevents oscillatory quarantine-release cycles.
Stabilization and quarantine therefore address oscillation at two scales: stabilization damps rapid alternation within an individual field by lengthening its effective decay time constant, while quarantine restricts the agent's operation when oscillation across fields is severe enough to compromise the reliability of its deliberation. The two mechanisms are complementary, and both rely on monitoring the recent update history rather than on any single observation.
Disclosure Scope
The emotional decay curves, the semantic hysteresis implemented through asymmetric increase and decrease rates, and the entropy-governed valence stabilization that progressively increases the effective decay time constant to damp oscillation in a named control field, together with the policy-configurable stabilization threshold and damping factor and the decay governance constraints that bound them, are disclosed in the cognition filing (U.S. Application No. 19/647,395 and its international counterpart). This article describes that disclosed mechanism. The scope extends to embodiments in which different named control fields carry different decay time constants and in which the stabilization stage is realized over alternative decay functions, provided the stabilization acts by lengthening the field's relaxation under policy-bounded constraints and remains a deterministic, lineage-recorded stage of the affective state update pipeline.
