Deterministic Affect Encoding and Update Mechanics

Mechanism

The affective state is represented as a fixed-width canonical vector whose dimensions correspond to enumerated affect primitives (for example, valence, arousal, trust, urgency, fatigue, and a small set of policy-specific extensions). Each dimension is encoded as a fixed-precision scalar with a defined range, a defined quantization step, and a defined saturation behavior. The vector header carries a version tag, a policy hash, and a lineage pointer to the immediately preceding state.

The transition function takes three inputs: the prior canonical vector, an observation record (also canonicalized and signed), and a policy reference identified by content hash. It produces a successor canonical vector and a lineage entry. The lineage entry contains the prior vector hash, the observation hash, the policy hash, the computed delta on each affected dimension, and the successor vector hash. The lineage entry is itself canonical and hashable; it forms the unit of audit.

Determinism is preserved by three invariants. First, all arithmetic occurs in fixed-point integer space; floating-point representations are excluded from the update path. Second, ordering is total: when an observation arrives, its position in the affective timeline is determined by a tuple of (logical clock, observation hash) rather than by arrival time at any particular substrate. Third, decay is computed as a deterministic function of logical-clock difference rather than wall-clock difference; the decay constants are policy-bound and are part of the canonical policy reference. A receiving substrate can therefore replay the lineage from any checkpoint and arrive at the same successor state, byte for byte, as the originating substrate.

Cross-primitive coupling is expressed through a coupling matrix carried in the policy. When a primary dimension is updated, the coupling matrix yields deterministic secondary updates on coupled dimensions (for example, prolonged high arousal damping the trust dimension). Coupling is bounded: the matrix is stochastic-row-normalized at policy compile time so that no single observation can saturate the entire vector. Saturation, when it does occur, is also deterministic: the dimension is clipped to its declared range and a saturation flag is recorded in the lineage entry.

Operating Parameters

The canonical vector width is policy-bound and is typically in the range of sixteen to sixty-four dimensions. Each dimension is encoded in sixteen bits of fixed-point precision, with the most significant bit reserved for sign and the remaining bits expressing magnitude in defined quantization steps. The vector is padded to the declared width even when a particular policy uses fewer primitives, so that wire format is stable across policies of the same generation.

Decay constants are expressed as half-life parameters in logical-clock units. Typical half-lives range from minutes (for transient arousal-class dimensions) to days (for trust-class dimensions). The decay function is a fixed-point approximation of exponential decay, computed with a lookup table whose contents are part of the policy hash. Two implementations using the same policy will produce identical decay outputs given the same elapsed logical-clock interval.

Lineage entries are bounded in size and are emitted at every update. Storage of the full lineage is policy-dependent: some policies retain only the most recent N entries plus a cryptographic Merkle accumulator over the discarded prefix, while others retain the full chain. In either case, the audit guarantee is preserved: any claimed successor state can be checked against the chain by replaying or by verifying the accumulator inclusion proof.

Update throughput is bounded by the canonicalization and hashing cost rather than by the arithmetic itself. On commodity hardware, sustained update rates in excess of one hundred thousand updates per second per core have been observed for sixteen-dimension vectors with sixty-four-byte observation records. Latency per update is dominated by the hash function and is typically below ten microseconds.

Alternative Embodiments

In one embodiment, the canonical vector is encoded in protobuf with a deterministic-serialization profile, enabling integration with existing telemetry pipelines that already depend on protobuf framing. In a second embodiment, the vector is encoded in a custom fixed-width binary format optimized for line-rate processing on network interfaces; this embodiment is preferred for in-line policy enforcement at the substrate boundary.

In a further embodiment, the policy reference is bound to a hardware-rooted key rather than to a content hash alone, so that policy substitution requires both repository access and the corresponding signing key. This embodiment supports regulated deployments in which the affect policy is itself subject to change-control review.

A streaming embodiment emits each lineage entry to a write-once log substrate at the moment of update, decoupling the update path from any retention decision. A batched embodiment accumulates lineage entries into segments and emits Merkle roots periodically, trading audit granularity for storage efficiency. Both embodiments preserve the determinism property; they differ only in lineage-emission cadence.

An embodiment supporting confidential affect carries the canonical vector through a homomorphic transform so that downstream processing can operate on the affective state without recovering primitive-level values. The transform is itself deterministic, and the lineage records the transform parameters so that re-derivation remains possible by a holder of the de-blinding key.

Composition With Other Subsystems

Deterministic affect encoding composes with the agent's policy engine: the policy reference that parameterizes the transition function is the same reference that gates downstream decision-making, so an audit of a decision can present the affective state and the policy under which it was produced as a single coupled record.

It composes with the agent's identity machinery: the canonical vector hash can be folded into the agent's continuity attestation, so that a substrate accepting a migrating agent can verify both the structural identity and the coupled affective state in a single attestation pass.

It composes with cross-agent coordination: when two agents exchange affective context (for example, in a negotiation or a hand-off), each can present a canonical vector and a lineage proof; the receiving agent can verify the lineage without trusting the sending substrate. This makes deterministic affect a building block for coordination protocols that must remain auditable across organizational boundaries.

Distinction From Prior Art

Prior art in affective computing has concentrated on inferring affect from observation (recognizing emotion in faces, voice, or physiology) and on generating affect-conditioned output (expressive synthesis). State-machine representations of affect exist, but they have generally been platform-specific, floating-point-based, and non-reproducible across implementations. The novel contribution is the discipline of deterministic encoding: byte-identical state machinery suitable for cryptographic binding and adversarial audit, with a lineage chain that survives substrate migration.

Determinism in the present sense is stronger than reproducibility-with-seed. A seeded stochastic system produces the same output only when both the seed and the implementation are controlled. The present mechanism removes stochasticity from the update path entirely, so that determinism is a property of the canonical specification rather than of any particular runtime configuration.

Failure Modes And Adversarial Considerations

A divergence between two implementations claiming the same policy is a first-class diagnostic event. Because the canonical specification permits a single correct successor, divergence implies that at least one implementation is incorrect or has been tampered with. The architecture surfaces divergence detection by sampling: receiving substrates periodically replay short lineage segments and compare the resulting hash against the claimed successor hash. A mismatch is recorded as a credentialed diagnostic and triggers escalation policy. This converts what would otherwise be a silent correctness bug into a loud, attributable governance event.

Replay attacks against the affect lineage are bounded by the logical-clock invariant. An adversary cannot inject a stale observation as a current one, because the observation hash is bound to its position in the timeline; injection at a different position produces a different successor and the divergence detector flags it. Reordering attacks are similarly bounded: the canonical timeline is a function of (logical clock, observation hash) tuples, and any reordering yields a different lineage chain with a different terminal hash.

Policy substitution is bounded by the policy-hash binding. A successor state is meaningful only relative to the policy under which it was produced; changing the policy mid-stream produces a discontinuity that the lineage records explicitly, with the prior-policy hash and the new-policy hash both present at the discontinuity entry. Audits that pin a particular policy can therefore detect any segment of the chain produced under a different policy without ambiguity.

Saturation-induced information loss is mitigated by the saturation-flag record: the lineage entry preserves the fact that an update was clipped, the dimension that clipped, and the magnitude of the unrealized change. Downstream consumers can therefore distinguish a state at saturation from a state that arrived at saturation by a different path, which matters for re-validation and for retrospective inference about agent stress.

Implementation Notes

Reference implementations target three substrate classes. A server-class implementation operates in user space on commodity Linux and reaches the per-core throughput cited above with mainstream cryptographic libraries. An edge-class implementation operates on constrained hardware with hardware-accelerated hashing and fixed-point arithmetic; per-update latency rises into the tens of microseconds but throughput remains adequate for typical edge-agent workloads. An embedded-class implementation operates on microcontroller hardware and trades vector width and lineage retention against cycle and memory budgets, while preserving the canonical wire format so that exported state remains comparable to that of richer substrates.

Test vectors accompany the canonical specification. Each vector is a triple (prior canonical vector, observation, policy reference) together with the expected successor canonical vector and lineage entry. A candidate implementation is conformant if and only if it reproduces every vector byte for byte. The vector set covers ordinary updates, decay-only transitions, coupling-driven secondary updates, saturation, and policy-discontinuity transitions. New vectors are added with each policy generation, and the conformance suite is itself versioned and hashed.

Operational deployments observe the architecture's behavior through three first-class metrics: divergence-detection rate, saturation rate, and lineage-storage growth. Healthy deployments show divergence rates indistinguishable from the sampling false-positive rate, saturation rates concentrated in expected high-arousal scenarios, and lineage growth proportional to update rate. Sustained departure from these patterns is a diagnostic signal independent of any individual decision the agent renders, and operators are encouraged to alert on these metrics as part of standard runbook practice.

Disclosure Scope

The disclosure covers the canonical encoding format, the deterministic transition function, the lineage-entry structure, the decay function and its policy binding, the cross-primitive coupling matrix, and the composition with policy, identity, and coordination subsystems. It covers the embodiments enumerated above and equivalents that preserve the determinism, lineage, and policy-binding properties. It does not claim particular affect primitives, particular decay constants, or particular policy contents; those are configuration choices made by adopters within the disclosed framework.