Affective Inheritance in Delegation Chains

Mechanism

The inheritance primitive operates at the moment of task spawn. When a parent agent P delegates a subtask T to a newly instantiated child agent C, the runtime invokes an inheritance function that takes as input the parent's current affective-state vector, the delegation policy attached to the spawn site, and the depth counter inherited from the parent's own delegation context. The function emits an inherited-affect vector that is installed as C's initial-condition modifier — not as C's active affective state, but as an additive bias against which C's own accumulating state is measured.

The inheritance function is the composition of three operators. The first is a mask operator that selects, on a per-dimension basis, which components of the parent's affective vector are eligible for transmission. The mask is defined by the delegation policy and reflects the structural relevance of each dimension to the subtask: an agent delegating a navigation subtask may transmit caution and curiosity dimensions while masking out social-affect dimensions that are not operative in the subtask. The second is an attenuation operator that scales the surviving dimensions by per-dimension factors strictly less than one. Attenuation enforces the bounded-transformation property: each hop reduces signal magnitude by a known factor, so cumulative signal decays predictably with depth. The third is a depth gate that suppresses any dimension whose configured maximum-depth threshold has been reached, hard-zeroing transmission past the policy-declared horizon.

The depth counter is incremented on every delegation hop and is carried in the spawn metadata. A chain-length cap is enforced at the runtime: a spawn that would push the counter past the cap is either rejected or proceeds with a fully zeroed inheritance vector, depending on policy. This cap is structural; it cannot be bypassed by an individual agent because the counter is maintained by the runtime and is signed into the spawn record.

A return channel completes the loop. When C reaches a milestone or terminates, a summary of its accumulated affective experience is made available to P's update function. P's policy determines what, if any, of the returned summary is incorporated into P's own affective state. The return channel is itself bounded: it transmits a summary, not the full trajectory, and it is subject to its own attenuation and masking under the parent's update policy.

Operating Parameters

The principal parameters are the per-dimension mask, the per-dimension attenuation factors, the per-dimension depth thresholds, the global chain-length cap, and the return-channel summary policy. Attenuation factors are typically chosen in the range 0.4 to 0.8 per hop, producing geometric decay that reaches operational insignificance within three to five hops for most dimensions. Per-dimension depth thresholds permit dimensions of strong structural relevance — for instance, safety-relevant caution in a delegated physical-action chain — to propagate further than dimensions of weaker relevance.

The global chain-length cap is set against the deployment's worst-case delegation topology. Typical caps in the range of six to twelve hops cover most operational task graphs while preventing pathological recursion. The cap interacts with the per-dimension thresholds: a dimension with a depth threshold of three hops effectively contributes nothing past hop three regardless of the global cap, and the global cap exists to bound total agent population rather than to bound affective signal directly.

The return-channel summary policy specifies the dimensions reported, the temporal aggregation (terminal value, peak value, time-weighted mean), and the gating conditions under which a return is emitted at all. Some delegations are configured fire-and-forget with no return; others emit returns only on anomalous termination; others emit on every milestone.

Alternative Embodiments

The disclosure contemplates embodiments in which the inheritance function is implemented as a learned model rather than as a hand-specified mask-and-attenuate composition. In such embodiments, the runtime supplies the parent state, the delegation context, and the spawn metadata to a small inheritance network that emits the inherited-affect vector directly. The bounded-transformation property is preserved by training the network under a constraint that bounds its output norm relative to its input norm.

Further embodiments admit multi-parent inheritance for child agents spawned to serve a coalition of parents. The inheritance function in these embodiments composes contributions from all parents under a coalition-policy mask that resolves dimension-level conflicts — for instance, by taking the mean, the median, the safety-conservative extremum, or a policy-weighted combination.

Additional embodiments specify time-decay on the inherited bias such that the child's initial-condition modifier fades over the child's runtime, ensuring that long-running children eventually operate under their own accumulated state rather than under the parent's transmitted bias. The decay schedule is a policy parameter and may be tuned against the expected child task duration.

An embodiment relevant to safety-critical fleets enforces a one-way propagation rule for specific dimensions: caution and risk-aversion dimensions are transmitted parent-to-child but never increase in the parent via the return channel beyond a policy-bounded delta, preventing positive feedback loops in which fleet-wide caution accumulates without operational basis.

Composition With Cognition Substrate

The inheritance primitive composes with the broader cognition substrate's task-graph representation. Each spawn record carries the inheritance metadata as an immutable annotation, permitting after-action audit of what affective context flowed into which subtask. The audit record is essential for diagnosing emergent behaviors in delegation-rich systems and for regulatory contexts that require explainability of agent decisions.

The primitive composes with the substrate's policy layer. Inheritance policies are first-class objects, versioned, signed, and attached to spawn sites at design time or at runtime via the policy-update primitive. A change in inheritance policy propagates to subsequent spawns without disturbing in-flight delegations.

The primitive further composes with the substrate's affect-update machinery. The inherited bias is treated by the child agent's update function as a distinguished input class, separate from the child's experiential affect; this preserves the operational semantics in which the child's own accumulating affect retains primary authority over decisions while the inherited bias acts as a structural prior. The substrate exposes the inherited-bias trajectory as observable telemetry, enabling operator visibility into the relative contribution of inherited and earned affect at every decision point.

The primitive composes with cross-system boundaries through a serialization contract that preserves mask, attenuation, depth, and chain identity when an inheritance signal crosses an organizational or vendor boundary. A child agent operated by a different vendor than the parent receives the inheritance vector under the same structural guarantees, enabling federated multi-agent deployments in which delegation crosses ownership boundaries without losing the bounded-transformation contract.

Prior-Art Distinction

Conventional multi-agent delegation frameworks transmit task parameters and authority but do not transmit affective-state context. Where affect-bearing systems exist in the literature, they typically maintain affective state per-agent without structural mechanisms for inter-agent affective transfer. Other lines of prior work have proposed shared blackboards and unrestricted broadcast of internal-state vectors, neither of which preserves the bounded-drift property or the per-dimension policy gating that the present disclosure requires. The novelty of the present disclosure is the bounded-transformation contract, the depth-gated mask architecture, the chain-length cap, and the return channel — taken together as a structural primitive that propagates experiential context with bounded drift, rather than either ignoring affect at delegation boundaries, broadcasting it without structure, or transmitting it without bound.

Failure Modes and Mitigations

Three failure modes are anticipated and structurally addressed. The first is signal collapse, in which aggressive attenuation across a long chain reduces the inherited bias to operational insignificance before the structurally relevant subtask is reached. The architecture mitigates by per-dimension threshold tuning that permits structurally important dimensions to attenuate more slowly, by selective chain-shortening primitives that allow a parent to bypass intermediate hops for affect transmission while preserving the task delegation chain, and by depth-aware attenuation schedules that apply different per-hop factors at different positions in the chain. A delegation policy that anticipates long chains can begin with mild attenuation in early hops and steepen attenuation only past a configured depth.

The second failure mode is policy poisoning, in which a delegation policy is constructed — accidentally or adversarially — to transmit affective signals that bias child agents toward decisions disfavored by the system operator. The architecture mitigates with policy signing, policy review at design time, and runtime gates that require any inheritance policy modifying a safety-relevant dimension to be co-signed by the safety authority. Inheritance policies are first-class auditable objects, and the audit record permits reconstruction of which policy version governed any given spawn.

The third failure mode is return-channel feedback instability, in which a return signal from a child triggers an update in the parent that is then transmitted to subsequent children, producing oscillation or runaway. The architecture mitigates with bounded update-magnitude policies in the parent, with rate limits on parent update from any single child, and with the optional one-way propagation rule for safety-critical dimensions. The combination ensures that the closed loop through delegation and return is contractive on the relevant dimensions and cannot amplify without bound.

Disclosure Scope

The disclosure teaches the inheritance function and its mask-attenuate-gate composition, the depth counter and chain-length cap, the return channel and its update-policy gating, the failure-mode mitigations, the alternative learned-network embodiment, the multi-parent coalition embodiment, the time-decay embodiment, the one-way-propagation safety embodiment, and the cross-vendor serialization contract. The scope encompasses delivery-fleet coordination, hierarchical organizational agents, safety-critical multi-agent systems, autonomous-vehicle coordination across multi-tier dispatch, and any deployment in which delegation chains span multiple hops and experiential context across those hops is operationally relevant. The disclosure further reserves application to humanoid-robotic team operations, to mixed human-and-agent task graphs in which selected affective dimensions cross the human boundary under explicit consent, to research and educational simulation environments in which inheritance behavior itself is the object of study, and to industrial process-control deployments in which delegated agents inherit operator-derived caution profiles before assuming local autonomy.