Affect-Modulated Discovery Traversal

Mechanism

A discovery object enters the semantic index at a seed anchor and walks the index by repeatedly scoring candidate transitions and selecting among them. In an unmodulated implementation, the transition scoring function is a pure function of the candidate anchor's semantic neighborhood description and the discovery object's query intent. The same query, executed from the same seed, always produces the same trajectory.

Affect-modulated traversal introduces the discovery object's affective field as an additional input to the transition scoring function. The affective field is a structured value carrying signed scalars on a fixed set of dimensions: novelty appetite, risk sensitivity, confidence, urgency, and fatigue, among others. Each dimension contributes an additive modifier to the base transition score for each candidate, where the modifier is computed from the interaction of the affect dimension and a corresponding feature of the candidate's neighborhood description.

For example, novelty appetite multiplies a candidate's unfamiliarity feature, defined as the inverse log frequency of prior visits to the candidate's neighborhood across recent traversals. Risk sensitivity multiplies a candidate's governance-uncertainty feature, derived from the proportion of items in the neighborhood whose policy attestation is missing or stale. Confidence multiplies a step-length feature, allowing high-confidence agents to take longer hops between anchors and short-circuit intermediate validation. Urgency multiplies a depth-discount feature, biasing toward shallower, faster-converging branches.

The composite transition score is the base score plus the bounded sum of affect modifiers, with the bound enforced by policy. The selection step picks the highest-scoring candidate, breaking ties by deterministic anchor ordering, and the chosen transition is recorded in the traversal lineage along with a snapshot of the affective field at the time of selection. This lineage record is what makes affect-modulated traversal auditable: every divergence from the unmodulated baseline can be attributed to a specific affect dimension and magnitude.

Operating Parameters

The modulation is governed by a small set of operating parameters that determine its expressive range and safety envelope. Per-dimension gain coefficients scale how strongly each affect dimension influences scoring; in safety-critical deployments these gains are tuned conservatively so that affect can perturb but not override the base scoring. A composite ceiling caps the absolute magnitude of the summed affect contribution as a fraction of the base score, typically thirty to fifty percent, ensuring that even an extreme affective state cannot fully invert the unmodulated ranking.

A floor on candidate eligibility ensures that affect cannot drive the score of a governance-required candidate below the selection threshold. Governance-required candidates are those whose inclusion is mandated by policy, regardless of agent state, and they are exempted from negative affect modifiers. This is the structural separation between exploratory modulation and governance constraint: affect shapes preference within the admissible set but does not redefine admissibility.

Decay constants govern how affective state evolves during traversal itself. A long traversal under sustained fear gradually erodes its narrowing effect as the agent accumulates evidence that the explored region is safe; conversely, repeated encounters with anomalous content can amplify risk sensitivity within a single discovery operation. These intra-traversal updates are themselves bounded by the same policy that bounds external affective updates, preventing runaway feedback.

Alternative Embodiments

In a multiplicative embodiment, affect modifiers scale the base score rather than adding to it, producing more pronounced divergences for high-magnitude affect states while preserving the relative ordering for neutral states. In a gated embodiment, affect modifies only the candidate filter, removing candidates that fail an affect-conditioned predicate before scoring proceeds against the unmodulated function. The gated form is useful in deployments where downstream consumers expect score values comparable to baseline.

A trajectory-ensemble embodiment runs multiple discovery objects in parallel, each seeded with a different sampled affective profile drawn from a distribution over the agent's recent affective history. The union of trajectories provides exploration coverage that no single profile would produce, and the divergence between trajectories serves as a measure of how affect-sensitive the current query is. Queries with low divergence are robust to affect; queries with high divergence are flagged for review.

A contrastive embodiment pairs each modulated traversal with an unmodulated shadow traversal and exposes both trajectories to the consumer. Downstream forecasting modules can then compare the two and either accept the modulated result, fall back to the baseline, or compute a forecast over the differential. This embodiment is preferred where the consumer needs explicit visibility into the affective contribution.

Composition With Other Subsystems

Affect-modulated traversal composes naturally with the semantic discovery subsystem because the modulation enters at a single, well-defined point: the transition scoring function. Existing index structures, anchor schemas, and neighborhood descriptors are unchanged. A semantic discovery deployment can be upgraded to affect-modulated traversal by replacing the scoring function and adding the affective field to the discovery object's structured state.

The composition with forecasting is more substantive. A forecasting module that consumes traversal trajectories as evidence must reason about the modulation that produced them, otherwise it conflates content-driven signal with affect-driven sampling bias. The lineage records emitted by affect-modulated traversal carry the affective snapshot, which the forecasting module uses to reweight evidence: a candidate that was selected because of high novelty appetite is not the same evidentiary signal as a candidate that was selected on its base score alone. Forecasts are conditioned on the affective profile of the traversals that fed them.

Composition with policy-bounded affective updates is what gives the entire pipeline its safety guarantees. Because every affect change passes through the bounded update path, the affective field that enters the scoring function is always within operational range, and the lineage that traces a forecast back to its source traversals also traces it back to authenticated affect changes. The end-to-end property is that no traversal can be steered by an affective state that the policy did not authorize.

Behavioral Signatures By Affective Profile

A fear-dominated profile, characterized by elevated risk sensitivity and depressed novelty appetite, produces traversals that hug regions of high prior visit frequency and low governance uncertainty. Step length contracts because confidence is depressed, and the trajectory tends to terminate quickly at the first anchor satisfying the query, even when continuation would reveal stronger candidates. The behavior is functionally analogous to a narrowed search aperture in a stressed human operator and is appropriate when the cost of error dominates the cost of incomplete coverage.

A curiosity-dominated profile, characterized by elevated novelty appetite without elevated risk sensitivity, produces broader traversals that revisit fewer anchors and explore lower-frequency neighborhoods. The trajectory tends to extend further before termination because the query satisfaction threshold is implicitly raised by the agent's preference for continued exploration. Index regions that an unmodulated traversal would never reach become part of the lineage, and the resulting telemetry exercises corners of the index that are otherwise undersampled.

A confidence-dominated profile produces accelerated traversal: longer hops, fewer intermediate validations, and shorter overall latency. The trade-off is reduced sensitivity to local irregularities, which is acceptable when the agent has prior evidence that the traversed region is well-formed. An urgency-dominated profile produces shallow, fast-converging traversals that prioritize any sufficient answer over the best available answer. These signatures are observable in the lineage and constitute a behavioral fingerprint by which an external auditor can classify the affective regime under which a given output was produced.

Distinction From Prior Art

Personalized search and recommendation systems incorporate user-specific signals into ranking, but those signals are static profile features or recent interaction history, not a structured affective state with bounded update semantics. Reinforcement-learning agents adjust exploration through epsilon-greedy schedules, entropy bonuses, or learned exploration policies, but those mechanisms operate on a single scalar exploration parameter without the dimensional structure that allows fear, curiosity, and confidence to produce qualitatively different traversal shapes.

The distinguishing combination here is structured multi-dimensional affect, bounded by signed policy, applied at a specific architectural location, recorded in lineage, and composed with downstream forecasting and governance subsystems that consume the lineage. No prior system simultaneously exhibits all of these properties.

Scope Of This Disclosure

This article discloses the mechanism, operating parameters, and alternative embodiments of affect-modulated discovery traversal as one component of the broader cognition system described in the parent disclosure. Implementations may vary the dimensional set, the modifier function form, the composition topology with downstream subsystems, and the embodiment form without departing from the inventive concept. The essential property is that an auditable, bounded, structured affective state modulates traversal at the scoring layer while leaving governance constraints unchanged, and that the resulting trajectories are distinguishable in lineage from those that an unmodulated system would have produced.

The disclosure of U.S. Provisional Application No. 64/049,409 further admits embodiments in which per-dimension gain coefficients, composite ceilings, and decay constants are themselves credentialed governance instruments rather than static configuration, allowing an authorized governance authority to retune the modulation envelope across a fleet of agents under a single signed update, with each retuning event recorded in the lineage chain and reversible through the same governance procedure that admitted it.