Policy-Bounded Affective Updates
by Nick Clark | Published March 27, 2026
Every affective update constrained by range bounds, rate limits, admissible triggers, update authority, and decay governance specified in the policy reference field.
What It Is
Every affective update is constrained by five governance parameters defined in the policy reference: range bounds that limit each dimension's minimum and maximum values, rate limits that cap how quickly a dimension can change, admissible triggers that define which event types can update which dimensions, update authority that specifies who can trigger updates, and decay governance that controls baseline return behavior.
No affective update can exceed these bounds regardless of the magnitude of the triggering event.
Why It Matters
Unbounded affective updates enable manipulation. An adversary that can trigger extreme events could push an agent's affective state to pathological extremes, effectively disabling normal function. Policy bounds ensure that even under adversarial conditions, each dimension remains within operational ranges.
Rate limits prevent rapid manipulation sequences that individually stay within range bounds but cumulatively drive the state to extremes faster than decay can compensate.
How It Works Structurally
The affective update function checks each proposed dimension change against the policy bounds before applying it. If the proposed new value exceeds the ceiling, it is clamped to the ceiling. If the rate of change since the last update exceeds the rate limit, the update is throttled. If the triggering event is not in the admissible trigger set for the affected dimension, the update is rejected.
These checks are performed atomically for each update, and the enforcement decision is recorded in lineage.
What It Enables
Provably bounded affective behavior. System operators can guarantee that no agent's affective state will exceed specified operational ranges, enabling formal safety analysis and regulatory compliance.
Domain-specific tuning where safety-critical domains use tight bounds while exploratory domains use wider bounds, all through policy configuration rather than architectural changes.
