Named Control Field Modulation Architecture

Mechanism

The affective state field is introduced as a seventh structural field of the semantic agent schema, alongside the intent field, context block, memory field, policy reference field, mutation descriptor field, and lineage field. It is a deterministic, policy-bounded data structure that encodes valence-weighted feedback derived from prior execution outcomes and environmental observations. It does not encode emotion in the phenomenological or subjective sense. It encodes a structured modulation vector that influences the agent's deliberation dynamics: how the agent weighs alternatives, tolerates ambiguity, persists under partial failure, and escalates under constraint pressure.

In one embodiment, the affective state field is organized as a structured modulation layer comprising a plurality of named control fields. Each named control field encodes a distinct dimension of the agent's dispositional orientation and governs a specific aspect of its deliberation behavior. The named control fields are not arbitrary labels. Each corresponds to a measurable modulation axis with defined semantics, value ranges, update rules, and governance bounds. Because the affective state field is a structural field rather than metadata, an annotation, or an external signal, every mutation to it participates in the same governance, lineage tracking, and policy enforcement that apply to all other agent fields.

The Named Control Fields

The named control fields of the affective modulation layer comprise, in one embodiment, at least the following dimensions. An uncertainty sensitivity field encodes the agent's current responsiveness to epistemic uncertainty in its environment: when elevated, the agent weights uncertain inputs more heavily and tends to defer or escalate rather than commit. An ambiguity tolerance field encodes the agent's capacity to operate where multiple interpretations of input are plausible and unresolved, permitting parallel candidate interpretations without forcing premature resolution. A novelty appetite field encodes the agent's disposition toward previously unobserved patterns, entities, or execution paths.

A persistence-under-partial-failure field encodes the agent's tendency to continue a line of execution when intermediate results indicate partial failure or degraded confidence, driving retry, adaptation, or reformulation rather than abandonment. An escalation-under-time-pressure field encodes the agent's tendency to escalate decision authority, request external input, or delegate when operating under temporal constraints. A risk sensitivity field encodes the agent's weighting of potential negative outcomes relative to potential positive outcomes when evaluating candidate mutations or execution paths. A cooperation disposition field encodes the agent's tendency to favor collaborative execution strategies, including delegation, resource sharing, and multi-agent coordination, over independent execution. A further embodiment depicts an attention sensitivity field among the named control fields of the modulation layer.

The Field Tuple

In one embodiment, each named control field is represented as a tuple comprising: a current magnitude value within a defined range; a decay rate governing how rapidly the field value returns toward a baseline in the absence of reinforcing stimuli; a policy-defined ceiling and floor bounding the permissible range of the field; and a timestamp recording the most recent update. Each named control field occupies a defined position in the fixed-schema structure and is independently readable, writable, and auditable.

The affective state field is persisted with the agent across execution cycles, delegation events, and substrate migrations, so the agent's modulation state is not lost when the agent moves between execution environments or is serialized for transport. Because each dimension is a distinct field with its own magnitude, decay rate, and bounds, the architecture can distinguish a behavior change caused by elevated uncertainty sensitivity from one caused by elevated risk sensitivity, rather than collapsing all dispositional state into a single fused score.

What the Fields Modulate

The named control fields modulate specific, enumerated targets within the agent's deliberation and execution pipeline. The targets are not open-ended. Each is a defined computational parameter whose value the affective state field adjusts within governance bounds. The affective state field does not create new capabilities, authorize new actions, or bypass policy constraints. It modulates the quantitative parameters that shape how existing authorized processes execute.

The enumerated targets include promotion thresholds, the minimum score or confidence required for a candidate to advance from one evaluation stage to the next; search breadth, the number of candidate alternatives explored at each decision point; branch growth rates, the rate at which new speculative branches are generated during forecasting; decay rates for unpromoted candidates, the rate at which non-promoted candidates are discarded from working memory or planning structures; escalation thresholds, the conditions under which the agent transitions from independent operation to delegation or help-seeking; persistence parameters, the number of retry or reformulation cycles attempted before declaring failure; delegation routing preferences, the preference ordering among available delegates; and mutation acceptance thresholds, the stringency of the validation gate applied to mutations proposed by an external inference engine. Elevated risk sensitivity or uncertainty sensitivity raises promotion and mutation acceptance thresholds; elevated novelty appetite or ambiguity tolerance widens search breadth; elevated persistence-under-partial-failure slows candidate decay.

Deterministic, Policy-Bounded Updates

Updates to the named control fields are deterministic: given the same agent state, the same environmental inputs, and the same policy configuration, the update function produces the same output. The update function operates on structured observations derived from the agent's execution environment, including repeated failure patterns, competing objectives, time pressure, novelty exposure, uncertainty levels from model confidence, and execution success patterns. Each dimension of the affective state vector is updated independently according to its own update rule, subject to policy-imposed bounds, and the update is recorded in the agent's lineage as a state mutation event with the input observations and resulting state change preserved for audit.

Every update is a policy-bounded mutation. The policy reference field specifies, per named control field, a set of constraints: range bounds, a minimum and maximum permissible value beyond which the computed value is clamped; rate limits, a maximum magnitude of change per update cycle, preventing discontinuous affective jumps even under an extreme triggering observation; admissible triggers, the defined set of observation types permitted to drive updates to that field, so observations outside the set are ignored; update authority, the entities or processes authorized to initiate updates; and decay governance, constraints on the decay parameters including minimum and maximum decay rates. On receiving an observation, the update function verifies the observation type is admissible for the field, computes the raw update, clamps it to the rate limit, applies it, clamps the result to the range bounds, and records the complete transaction in lineage.

Decay, Hysteresis, and Stabilization

Each named control field is governed by a decay curve that determines how its value returns toward baseline in the absence of reinforcing stimuli. In one embodiment the decay function is an exponential with a configurable time constant, where the field value relaxes from its value immediately after the most recent update toward a policy-defined resting value over time. Different named control fields may have different time constants: 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 modulation layer exhibits semantic hysteresis, a property whereby the current affective state depends not only on current observations but also on the trajectory of prior states. Hysteresis is implemented through asymmetric update rules: in one embodiment, negative-valence updates driven by failure, uncertainty, or threat apply at a higher rate than positive-valence updates driven by success or stability, producing a built-in caution bias. Entropy-governed valence stabilization is applied to prevent oscillatory behavior: when a field exhibits rapid alternation between elevated and suppressed values, the stabilization mechanism progressively increases the effective decay time constant to damp the oscillation, with the stabilization threshold and damping factor configurable by policy.

Modulation Without Governance Override

A strict separation of concerns is maintained between the named control fields and the governance infrastructure. The affective state field modulates how the agent thinks, but does not determine whether the agent is permitted to act. It cannot create authority the agent does not possess, bypass policy constraints, validate truth claims, or authorize execution that governance has denied. The affective state field is not an input to the governance gate: even at maximal confidence disposition and minimal risk sensitivity, the gate independently determines whether the proposed action satisfies all policy requirements.

This separation operates across distinct dimensions. On authority, an agent with elevated cooperation disposition still cannot delegate outside its policy-defined delegation scope. On truth validation, an agent with suppressed uncertainty sensitivity does not thereby treat uncertain information as verified. On policy compliance, policy-imposed ceilings on field values and execution scope limitations remain inviolable regardless of the agent's modulation state. On trust slope validation, the cryptographic lineage trajectory is computed and validated independently of affective state. The named control fields adjust the sensitivity parameters of these processes within bounds, never the structural requirements themselves.

Disclosure Scope

The named control field modulation architecture, comprising the affective state field as a structured modulation layer of independently readable, writable, and auditable named control fields, the enumerated fields including uncertainty sensitivity, ambiguity tolerance, novelty appetite, persistence-under-partial-failure, escalation-under-time-pressure, risk sensitivity, cooperation disposition, and attention sensitivity, the field tuple of current magnitude, decay rate, policy-defined ceiling and floor, and update timestamp, the deterministic and policy-bounded update function with its range bounds, rate limits, admissible triggers, update authority, and decay governance, the enumerated modulation targets, and the decay curves, semantic hysteresis, and entropy-governed stabilization, is disclosed in the cognition filing (U.S. Application No. 19/647,395 and its international counterpart) in the Affective State chapter. This article describes that disclosed mechanism. The scope extends to deployment-specific named control fields registered under the same fixed-schema tuple shape and governance bounds, and to alternative decay forms and update rules, provided each named control field remains independently bounded, audited in lineage, and unable to override governance.