The gap

AI systems do not monitor their own behavioral consistency across time. An agent can contradict its previous commitments, violate its stated values, and produce outputs that conflict with its established patterns, and no internal mechanism detects or corrects the deviation. Consistency checking, where it exists at all, is external: a human reviewer, a separate validation system, or a post-hoc audit.

Autonomous agents operating over extended periods therefore accumulate behavioral drift with no internal corrective signal. The longer they run, the less reliable their consistency becomes, and no one — including the agent itself — knows when the deviation began or how far it has progressed.

The invention

A three-domain self-monitoring model. Personal integrity tracks consistency with the agent's own normative commitments. Relational integrity tracks consistency in its interactions with other agents. Systemic integrity tracks consistency with the broader governance framework. A deviation function, D=(N−T)/(E×S), quantifies the gap between normative state and actual behavior, scaled by exposure and sensitivity. When deviation exceeds threshold, corrective pressure is generated automatically.

The coherence trifecta — empathy, self-esteem, and integrity — operates as a unified control loop. Empathy provides sensitivity to external state, self-esteem provides sensitivity to internal evaluation, and integrity provides the normative anchor. With these three signals coupled, deviation in one domain generates corrective pressure through the others, so the agent self-corrects rather than drifting.

The inventive step

Self-correction becomes a structural property of the agent rather than an external review function. Prior approaches treat consistency as something checked from outside, after the fact; here the deviation function is internal, quantified, and continuously coupled to corrective pressure across three distinct normative domains.

Coping intercepts model the failure modes of this loop. When coherence is disrupted — by excessive empathic load, by collapsed self-evaluation, or by normative conflict — behavior shifts to characteristic patterns that are structurally predictable and diagnostically identifiable. The system does not merely detect incoherence; it classifies the type of failure and its structural cause.

Alone, and in composition

On its own, the model serves any setting where an autonomous agent must remain accountable to its own commitments over long horizons: autonomous-vehicle ethics, trading under normative consistency, legal and policy advisory agents, and regulatory audit replay. The deviation function and coping intercepts give each domain a quantified, inspectable record of where and why behavior departed from its norms.

In composition, integrity supplies the normative anchor for the wider platform. Coupled with empathy and self-esteem as the coherence trifecta, it closes the control loop that lets agents elsewhere in the system detect drift, classify their own failure modes, and generate corrective pressure without external supervision.