Affective State as Seventh Canonical Field

What It Is

The affective state field is the seventh canonical field in the semantic agent schema. It encodes a deterministic, policy-bounded data structure that captures valence-weighted feedback across multiple dimensions: uncertainty sensitivity, ambiguity tolerance, novelty appetite, persistence, escalation, risk sensitivity, and cooperation disposition.

Each dimension is an independently addressable numeric field with defined range bounds, update rules, and decay characteristics. The affective state field is not a simulation of emotion. It is a structured modulation layer that adjusts how the agent evaluates candidates, prioritizes speculation, and responds to environmental signals.

Why It Matters

Without an affective state field, agents evaluate every situation with identical sensitivity. An agent that just experienced repeated failures treats the next candidate mutation with the same openness as one that has experienced consistent success. This produces brittle behavior: the agent cannot learn caution from negative experience or confidence from positive outcomes.

Adding affect as a canonical field means that cumulative experience directly modulates future evaluation. Risk sensitivity increases after adverse outcomes. Novelty appetite decreases under sustained uncertainty. Cooperation disposition adjusts based on delegation history. These modulations are not heuristics applied externally. They are structural properties of the agent that travel with it across substrates.

How It Works Structurally

When an event occurs that affects the agent, the affective update function computes new values for each relevant dimension based on the event type, the current dimension values, and the governing policy. The update is deterministic: given the same agent state and event, the same affective output is produced.

Each dimension stores its current magnitude, a timestamp of last update, and policy-defined ceiling and floor values that prevent any dimension from exceeding governed bounds. The affective field is readable by other cognitive subsystems including the confidence governor and the forecasting engine, creating cross-primitive feedback loops.

Decay functions operate continuously, pulling each dimension toward its policy-defined baseline at rates that may differ between positive and negative valence. The entire field is serialized with the agent during migration and validated against lineage on arrival.

What It Enables

The seventh canonical field enables agents that develop nuanced behavioral profiles over time. An agent operating in a high-uncertainty environment gradually adjusts its risk sensitivity and ambiguity tolerance, producing behavior that adapts to operational context without external reconfiguration.

Multi-agent systems gain richer coordination because each agent's affective state is visible to governance processes. Delegation decisions can account for a child agent's current volatility. Fleet-level monitoring can detect affective convergence or divergence patterns across agent populations.