Affect-Modulated Trust Slope Validation

Mechanism

The trust slope of a candidate delegate is computed as the time derivative of a credentialed-observation series, where each observation carries a credential weight reflecting the source's standing in the agent's policy regime. The slope is evaluated over a policy-defined window and is decomposed into magnitude (how fast the evidence is changing) and direction (whether the change favors or disfavors the candidate). A second, longer window provides the sustained-slope baseline used to distinguish transient excursions from regime change.

The validation function consumes the candidate's slope tuple and the evaluating agent's affective vector. It produces a strictness threshold that the candidate must meet before delegation is admitted. The threshold is computed as a base value, set by deployment policy, modified by a bounded function of the relevant affect dimensions: uncertainty sensitivity, risk sensitivity, and cooperation disposition. Elevated uncertainty or risk sensitivity raises the threshold, demanding stronger continuity evidence; elevated cooperation disposition with low risk sensitivity lowers the threshold, admitting candidates with weaker continuity. The modifier is bounded above and below by policy-defined limits, so the threshold cannot be raised to a level that blocks all delegation, nor lowered to a level that bypasses validation entirely.

A sudden trust drop — a sharp negative excursion in the short-window slope — triggers a caution response in the affective vector through the affect-update pathway. This raises uncertainty and risk sensitivity for a policy-defined recovery interval, which in turn raises the validation threshold for subsequent delegation evaluations. Sustained positive trust, observed across the longer baseline window, has the opposite effect: it relaxes uncertainty sensitivity and admits a broader class of delegates. The coupling is bidirectional but asymmetric — caution responses are fast-onset and slow-decay, openness responses are slow-onset and fast-decay — reflecting the asymmetric cost structure of delegation errors.

Operating Parameters

The short-window slope window, the longer baseline window, the caution-response onset and decay constants, the openness onset and decay constants, the threshold modifier function, and the bounding limits are all deployment parameters. They are published as part of the agent's policy regime and are auditable. No parameter is implicit or hidden; the entire validation behavior of the agent is reconstructible from the parameter set, the affect vector history, and the candidate's observation series.

The threshold modifier is a smooth, monotonic function of the affect dimensions within the policy bounds. Smoothness ensures that small affective fluctuations do not produce abrupt changes in delegation behavior; monotonicity ensures that the direction of affect-driven modulation is predictable. The function is parameterized so that operators may tune the strength of affective coupling without changing its structural properties.

Bounding limits prevent two failure modes. The upper bound prevents a runaway caution loop in which a single bad delegation experience drives uncertainty so high that no subsequent delegation can pass validation. The lower bound prevents a complacency loop in which sustained positive experience drives the threshold below a minimum acceptable level. The bounds are policy-defined and are typically set so that the threshold range covers approximately one decade of slope-magnitude requirement.

Alternative Embodiments

In a first embodiment, the threshold modifier is a closed-form linear combination of affect dimensions with policy-defined coefficients. In a second embodiment, the modifier is a small lookup table indexed by quantized affect bins, providing fully deterministic and trivially auditable behavior. In a third embodiment, the modifier is a learned function trained on a corpus of delegation outcomes labeled with evaluator affect state, with the learned function constrained to satisfy the smoothness, monotonicity, and bounding properties of the policy.

Trust slope itself may be computed as a simple linear regression over the credentialed-observation window, as an exponentially weighted derivative, or as a Kalman-filter-derived rate estimate. The choice is operational and is independent of the affect-coupling mechanism.

The caution and openness responses may be implemented as direct affect-update events injected by the trust subsystem, or as separate state variables in the affective vector dedicated to delegation context. Direct injection composes the trust signal into the general affective regime of the agent; dedicated variables isolate delegation context from other affective influences.

Composition with Adjacent Mechanisms

The mechanism composes with the affective state substrate, since the modulator function consumes the affective vector through the published interface and emits update events through the same interface. It composes with the disruption-modeling early-warning system, since trust slope excursions appear as one of the diagnostic axes monitored for cross-axis lock; a coordinated trust drop across multiple delegates can be detected as a precursor to broader system disruption. It composes with the integrity-coherence axis, since the bounding limits on the threshold modifier are themselves integrity constraints that the system enforces continuously.

Within a federation of agents, each agent's trust slope evaluations of shared delegates are independent, but the underlying credentialed-observation streams may be shared. Each agent therefore reaches its own threshold from its own affective context applied to common evidence, producing federation-level diversity in delegation behavior without divergence in the underlying evidence base.

Prior-Art Distinction

Conventional trust evaluation in delegation systems uses fixed thresholds, optionally parameterized by static role or domain, applied to a scalar trust score. Such systems do not respond to the evaluator's experiential context; an agent that has just suffered a delegation failure validates the next candidate with the same strictness as an agent in a long-established stable regime. This is operationally suboptimal because it ignores information — the recent failure is informative about the candidate population — and it is auditably indistinguishable from arbitrary threshold setting.

Reputation systems that adjust thresholds based on aggregate network history likewise lack evaluator-specific context. The mechanism disclosed herein is structurally different: the threshold is a function of the evaluator's own affective vector, which is itself a function of the evaluator's own experience series. The coupling is bounded, auditable, and reversible, and the response asymmetry between caution and openness is a deliberate design property rather than an emergent artifact.

Implementation Considerations

Three implementation considerations bear on practical deployment. The first is recovery from a caution lock. When sustained negative trust events drive uncertainty and risk sensitivity to their upper bounds, the validation threshold rises to its policy maximum and delegation effectively halts. Recovery requires either time-based decay of the affective excursion or an explicit operator override. The architecture supports both: the affective decay constants are tuned so that a single negative excursion clears in a bounded recovery interval, and the operator policy may include an override path that admits a low-strictness delegation under elevated audit, allowing fresh positive evidence to enter the slope computation and begin natural recovery.

The second consideration is gaming resistance. A delegation governance system that responds to the evaluator's affective state could in principle be manipulated by an adversary that engineers affective conditions favorable to the adversary's candidate. The architecture mitigates this through the bounding limits and through the auditability of the affective trajectory: an evaluator whose affect state has been driven outside its expected envelope is detectable through the integrity-coherence axis, and the bounding limits prevent any single excursion from collapsing the threshold to a fully permissive level. Adversarial pressure can shift delegation behavior within the bounded range but cannot break out of it.

The third consideration is auditability of denied delegations. When the modulator raises the threshold and a candidate is denied that would have been admitted under the base threshold, the system records the affective vector, the modifier value, the threshold delta, and the candidate's slope tuple. This record permits post-hoc review of whether the affect-driven denial was appropriate, supports operator tuning of the modifier function, and provides the substrate for regulatory inspection in deployments where delegation decisions must be explainable.

The mechanism is also responsive to network-level events without requiring centralized coordination. When a system-wide incident produces correlated negative trust signals across many evaluating agents, each agent's caution response is independently triggered by its own observation series, and the network as a whole exhibits a coordinated tightening of delegation strictness. As the incident clears and positive observations accumulate, openness recovers asymmetrically through the slow-onset, fast-decay structure, returning the network to its baseline delegation regime without operator intervention.

Disclosure Scope

The disclosure encompasses any delegation governance system in which a trust slope, computed as a time-resolved gradient of credentialed observations, is validated against a strictness threshold that is modulated by the evaluating agent's affective state vector through a bounded, policy-published function. It encompasses any embodiment of the slope computation, any embodiment of the modifier function consistent with the smoothness, monotonicity, and bounding properties, and any composition with adjacent affect-substrate, disruption-modeling, or integrity-coherence subsystems.

The disclosure does not encompass fixed-threshold delegation systems, network-aggregate reputation systems without evaluator-specific affective coupling, or systems in which the threshold modifier is unbounded or hidden. The boundary is the bounded affective coupling: a system in which delegation strictness does not respond, in a published and auditable way, to the evaluating agent's accumulated experiential context falls outside the scope of this disclosure.