Affect-Modulated Discovery Traversal

Mechanism

Each discovery object instantiates a structured affective state vector whose components include, at minimum, curiosity, caution (or fear), confidence, frustration, and novelty appetite. These components are not opaque scalars but typed fields with declared ranges, declared update semantics, and declared influence channels into the traversal scoring function. The state vector is initialized at the start of the discovery session from a combination of operator-supplied seeding, governance-declared defaults, and prior-session continuity if a continuity token is presented.

At each traversal step, the discovery object proposes a candidate set of next-anchor transitions drawn from the local neighborhood of its current position in the index. Each candidate carries intrinsic features (semantic distance, anchor type, governance class, historical traversal frequency) and contextual features (the trajectory taken to reach the current position, the elapsed depth of the traversal, the residual budget). The scoring function combines these features with the current affective state vector to produce a composite admissibility-weighted preference over the candidate set.

The affective influence on scoring operates through declared channels. Curiosity multiplies the weight given to semantic-distance-novel candidates, broadening the effective branching factor. Caution multiplies the weight given to candidates lying within high-corroboration neighborhoods of previously productive anchors, narrowing the effective branching factor and biasing toward exploitation. Confidence modulates the depth horizon, permitting the discovery object to defer consolidation steps and pursue longer inferential chains before pausing. Frustration, accumulated under repeated low-yield steps, raises a strategy-change pressure that can flip the curiosity-caution balance and trigger a structural reset of the traversal trajectory. Novelty appetite governs willingness to cross governance-class boundaries within policy-permitted bounds.

After each step's outcome is observed, the affective state is updated. Encountering a high-relevance anchor decreases curiosity drive (the local neighborhood has paid out) and increases confidence. Encountering a dead end (an anchor whose continuation candidates all score below a viability threshold) increases frustration. Crossing a governance boundary cleanly increases confidence and modestly decreases caution; encountering a denied transition increases caution and decreases novelty appetite. The update rules are declared and policy-governed, not learned in an unconstrained manner, so that the affective dynamics remain auditable.

Critically, the affective layer modulates only the scoring of options that are already governmentally permissible. It cannot override the admissibility gate, cannot relax governance requirements, and cannot induce traversal into regions whose access predicates have not been satisfied. The affective layer's effect is restricted to reweighting choices among admissible candidates and to triggering policy-permitted strategy changes such as backtracking, consolidation, or session-level termination.

Operating Parameters

Each affective component carries a declared range, typically normalized to a unit interval, with declared decay and accumulation rates. Decay rates govern how quickly an unreinforced affective component returns to its baseline; accumulation rates govern the magnitude of update per qualifying traversal event. A short-decay curiosity field produces bursty exploration; a long-decay curiosity field produces sustained exploratory campaigns punctuated by exploitation phases.

The strategy-change threshold on accumulated frustration determines how long the discovery object will persist in a low-yield trajectory before triggering a structural pivot. Tight thresholds produce nimble strategy changes appropriate to broad, shallow indexes; loose thresholds produce stubborn, deep traversal appropriate to indexes where productive yield is sparsely distributed and reachable only after extended traversal.

The depth-horizon multiplier driven by confidence governs how many steps the discovery object may take before pausing for consolidation. Consolidation involves summarizing the trajectory so far, comparing the summary against the discovery's declared objective, and emitting a partial result for operator review or downstream agent consumption. A higher multiplier permits longer autonomous excursions; a lower multiplier produces tighter operator-in-the-loop discipline.

The novelty-appetite ceiling caps the affective component's maximum value and thereby caps how aggressively the discovery object will pursue speculative transitions even under maximally curious states. The ceiling is a governance-declared parameter and is one of the principal levers by which deployments tune the trade-off between exploratory yield and traversal cost.

Continuity-token policy declares whether and how affective state persists across discovery sessions. Sessions may be configured for full continuity (the object resumes with the prior session's terminal affective state), partial continuity (selected components carry forward, others reset), or no continuity (each session begins from declared defaults). Continuity policy interacts with the broader identity and provenance discipline of the semantic-discovery substrate.

Alternative Embodiments

In a first alternative embodiment, the affective state vector is augmented with domain-specific components beyond the canonical five. Discovery objects operating in clinical, legal, or scientific domains may carry skepticism, deference, or rigor components whose update rules and influence channels are tailored to the domain's epistemic norms. Domain-specific components are declared in the deployment's affective schema and participate in scoring through the same channel mechanism as the canonical components.

In a second alternative embodiment, the affective state is shared across a cooperating ensemble of discovery objects pursuing related objectives. Ensemble-shared affect permits one object's frustration to inform another's caution, and one object's confidence to license another's depth. The sharing topology is policy-declared and may range from full broadcast within the ensemble to pairwise exchange along a declared coordination graph.

In a third alternative embodiment, affective updates are conditioned not only on traversal outcomes but on operator interventions. An operator who confirms a partial result raises confidence and reduces caution; an operator who rejects a partial result raises caution and frustration. This embodiment integrates the human-in-the-loop into the affective dynamics directly, rather than treating operator feedback as an out-of-band signal.

In a fourth alternative embodiment, the affective state participates in lineage. Each emitted result carries the affective state under which it was produced, so that downstream consumers can condition their treatment of the result on the affective profile of its production. A result produced under high curiosity and low caution carries a different epistemic weight than a result produced under high confidence and high rigor, and lineage carries this distinction forward.

In a fifth alternative embodiment, the affective scoring channels are themselves staged so that early-session traversal weights curiosity more heavily and late-session traversal weights confidence and consolidation. The staging schedule is policy-declared and supports deployments where the desired strategy profile is known a priori from the discovery objective's structure, such as literature-survey objectives that benefit from broad early sweeps followed by depth, or triage objectives that benefit from disciplined exploitation throughout.

In a sixth alternative embodiment, the affective state is exposed through a structured operator-facing surface that permits direct inspection and, within policy-declared bounds, direct adjustment. Operators may, for example, manually elevate caution when the discovery is approaching a sensitive boundary, or manually elevate curiosity when the discovery has settled too quickly into exploitation. Operator adjustments are themselves credentialed events recorded in lineage so that human influence on the affective trajectory is auditable.

Composition

Affect-modulated traversal composes with the admissibility gate, the governance substrate, and the lineage substrate of the broader semantic-discovery subsystem. The admissibility gate enforces what is reachable; the affective layer biases choice among reachable candidates. This separation is structural: the gate is policy-declarative and non-overridable, while the affective layer is dynamic and experience-driven. Their composition guarantees that no affective state, however extreme, can produce a policy-violating traversal.

Composition with the governance substrate occurs through declared parameter retrieval. The decay rates, accumulation rates, strategy-change thresholds, depth-horizon multipliers, and novelty-appetite ceilings are all retrieved from the deployment's policy object at session initiation and may be re-retrieved on policy updates. This composition ensures that affective behavior is governable rather than implementation-buried.

Composition with the lineage substrate occurs through the emission of affective trajectories alongside traversal trajectories. The lineage record for a discovery session contains both the sequence of anchors visited and the sequence of affective states traversed, permitting full reconstruction of why the discovery object made the choices it made. This is essential to the auditability commitments that distinguish the disclosed architecture from opaque heuristic search.

Prior-Art Distinctions

Heuristic search literature has long employed parameters analogous to exploration-exploitation balance, simulated-annealing temperature, and tabu-list memory. These parameters are typically static or annealed on declared schedules and lack the structured, multi-component affective semantics disclosed here. The disclosed mechanism differs in that the affective state is a structured, named, and governance-declared object whose components carry distinct semantics and distinct influence channels rather than a single scalar tuning knob.

Affective-computing systems in human-computer interaction model user affect to adapt interface behavior. The disclosed mechanism inverts this relationship: the affective state belongs to the discovery object itself, not to the user, and its purpose is to shape the object's traversal strategy rather than to adapt presentation. The composition with admissibility and governance substrates is also absent from conventional affective-computing systems, which generally operate without auditable lineage of affective trajectories.

Reinforcement-learning agents using intrinsic-motivation signals (curiosity-driven exploration, novelty bonuses) share the spirit of allowing agent state to shape exploration. The disclosed mechanism differs in being declarative rather than learned, in carrying multiple distinct affective components with declared semantics, in operating under a hard admissibility gate, and in participating in credentialed lineage. These structural distinctions matter for deployments where auditability and governance are non-negotiable.

Disclosure Scope

The disclosure encompasses methods, systems, and computer-readable media implementing affect-modulated traversal of a semantic-discovery index by a discovery object carrying a structured affective state vector with declared components, declared update rules, and declared influence channels into a candidate-scoring function. The disclosure includes embodiments with canonical and domain-specific affective components, embodiments with single-object and ensemble-shared affect, embodiments with and without operator-conditioned updates, and embodiments with and without affective-state lineage emission.

The disclosure further encompasses the composition of the affective layer with non-overridable admissibility gates, with policy-declared parameter retrieval, and with credentialed lineage substrates. The Cognition Patent establishes priority for the semantic-discovery subsystem within which affect-modulated traversal operates, and the disclosed mechanism is not limited to any particular index modality, anchor type, or domain of application.