Mechanism
Counter-action selection is the response stage of the adversarial-intent inference mechanism. An adversarial-entity detector produces governance-credentialed observations of entities exhibiting adversarial signatures; an adversarial-intent classifier maps detected entities to a hostile-intent taxonomy; a cross-domain adversary classifier assigns detected adversaries to domain-appropriate adversary classes; an inferring-authority credential evaluator weights the inferences by the inferring agent's authority and track record; and a hostility-profile-integration evaluator combines inferred adversarial intent with admitted hostility-profile signals to produce composite hostility estimates. The counter-action selector then produces a governance-policy-defined graduated counter-action, and a lineage recorder records each inference, classification, counter-action selection, and downstream consequence.
The hostile-intent taxonomy admits a plurality of categories operable across civilian and defense domains, including an offensive category indicating preparation or execution of attack, a defensive category indicating protection of an adversarial asset, a pursuit category indicating persistent targeting-following, a reconnaissance or surveillance category, a deceptive category indicating masquerading signals, a coordination category, a harassment category, an opportunistic-predation category, and any governance-policy-defined hostile-intent category. The detected adversarial signatures themselves span civilian-vehicular, unmanned-aerial, maritime, aircraft, robotic and industrial, pedestrian and personal-agent, cyber-physical, and defense-domain categories, along with composite multi-domain signatures.
The counter-action selector admits graduated response per the graduated response modes of Chapter 6 and Chapter 13 §13.9 rather than a single fixed reaction. The selected counter-action is admissibility-evaluated against the composite framework of Chapter 4 with governance-policy-defined authority, jurisdictional, laws-of-armed-conflict, civilian-safety, due-process, and use-of-force parameters constraining the admissible counter-actions per domain. Cross-domain coherence per Chapter 4 is applied to the adversarial-intent inferences before a counter-action is admitted.
Each counter-action is lineage-recorded, supporting command audit, after-action review, legal review, and regulatory-compliance review. The lineage records the inference, the classification, the counter-action selection, and the downstream consequence, so a counter-action commit is reconstructable from its recorded lineage together with the contributing observations.
Counter-Action Modes
The graduated counter-action set is enumerated by governance policy across civilian and defense contexts. It includes evasive-maneuver actuation per Chapter 6, such as civilian evasive driving, flight-path deviation, vessel course-change, or robotic workspace-clearance. It includes governance-credentialed evasive-routing coordinated with infrastructure agents to produce route-plan changes that avoid the adversarial entity, and authority-notification broadcasting governance-credentialed observations to law-enforcement, regulatory, public-safety, or coalition authorities.
The set further includes collective-warning emission broadcasting credentialed adversarial-presence observations to nearby agents through the governed mesh; target-protective routing for units that are the identified target, including rerouting to governance-credentialed safe-harbor locations; and de-escalation-coordinated response adjusting coordination margins, speed, and engagement distance per the de-escalation-responsiveness attribute of the adversarial operator's hostility profile.
Counter-targeting actuation is admitted only where governance-policy-admissible, including defense contexts with appropriate governance-credentialed authority and civilian self-defense contexts admissible under applicable jurisdictional authority. Additional modes include threat-reporting to coalition mesh participants, mission-disengagement with lineage of the disengagement decision, mission-reprioritization redirecting an in-flight munition or actively-operating unit to honor harm-minimization, counter-deception emission contradicting adversarial deceptive signals, bystander-alerting emission, escalation-to-authority handoff transferring coordination with the intercepted adversarial observation lineage, composite responses combining two or more counter-actions, and any governance-policy-defined counter-action.
Each counter-action is admissibility-evaluated against the composite framework of Chapter 4 with governance-policy-defined authority, jurisdictional, laws-of-armed-conflict, civilian-safety, due-process, and use-of-force parameters constraining the admissible counter-actions per domain. Each counter-action is lineage-recorded, supporting command audit, after-action review, legal review, and regulatory-compliance review.
Alternative Embodiments
In a stage-gated embodiment, the counter-action executes in a sequence of stages with admissibility re-evaluation between stages, enabling interruption or modification between stages per the stage-gated actuation mode of Chapter 6. This embodiment is appropriate for counter-actions whose side-effects are sensitive to changing environmental conditions, for example, an evasive route that traverses a region whose hostility classification may evolve during traversal.
In a consultative or advisory embodiment, the counter-action is presented through a less-autonomous graduated-actuation mode before physical execution. As composite admissibility rises or falls, the graduated-actuation mode selector transitions the response through increasingly or decreasingly autonomous modes rather than forcing a binary permit-or-deny outcome.
In a federated embodiment, counter-actions coordinate across coalition mesh participants. Threat-reporting and collective-warning emissions are broadcast through the governed mesh, and escalation-to-authority handoff transfers coordination to governance-credentialed emergency-response or law-enforcement authorities with the intercepted adversarial observation lineage.
In a learning embodiment, a verification feedback loop compares inferred intent against observed outcome and refines the inference functions through the training governance primitive of Chapter 12. An inference-function track-record maintainer updates the inference function's reputation per Chapter 28 based on verification outcomes, and an inference-function refinement engine produces adaptation artifacts.
In a civilian embodiment scaled for non-defense protective contexts, the same mechanism applies to civilian-vehicular adversarial signatures such as road-rage behavioral patterns, to unmanned-aerial-system harassment, to maritime piracy-approach trajectories, and to pedestrian persistent-shadowing behavior. Counter-targeting actuation remains admissible only where governance-policy-admissible, including civilian self-defense contexts admissible under applicable jurisdictional authority.
Composition
Counter-action selection is not a standalone subsystem; it composes with the other governance and observation primitives of the governed mesh. The adversarial-intent inference mechanism extends the cooperative intent primitive and the hostility profile mechanism, integrating inferred adversarial intent with admitted hostility-profile signals to produce composite hostility estimates. The composition surfaces are lineage-preserving, so each relationship is auditable rather than emergent.
Counter-action selection composes with the inferring-authority credential evaluator, which weights adversarial-intent inferences by the inferring agent's authority and track record per Chapter 28, and with the composite admissibility evaluator, which applies cross-domain coherence per Chapter 4. The hostility-profile-integration evaluator combines inferred adversarial intent with admitted hostility profile signals, and the resulting counter-action is constrained by the governance-policy-defined parameters of its domain.
The lineage recorder composes with the governed mesh's audit and broadcast channels and with after-action review, legal review, and regulatory-compliance review. The lineage recorder records each inference, classification, counter-action selection, and downstream consequence, so a counter-action commit is reconstructable from its recorded lineage together with the contributing observations.
Prior-Art Distinction
Prior advanced driver assistance systems infer other-unit behavior from onboard sensors without governance chain integration, whereas the present primitive produces lineage-recorded inferred-intent observations. Prior driver-intent-prediction research produces probabilistic estimates without authority credentialing or attestation, whereas the present primitive produces governance-credentialed inferences with inference-function authority attribution. Prior architectures do not integrate adversarial-intent inference with cooperative intent sharing, whereas the present primitive unifies both under a shared architectural mechanism.
The architecture disclosed here treats the counter-action as a governed observation. The counter-action is selected by governance policy, admissibility-evaluated against the composite framework, and lineage-recorded with its inference, classification, selection, and downstream consequence. The graduated response modes replace a binary permit-or-deny reaction, and the inferring-authority credential evaluator weights each inference by the inferring agent's authority and track record.
Disclosure Scope
The disclosure covers an adversarial-intent inference mechanism operable across civilian, commercial, industrial, emergency-response, and defense domains rather than being scoped to any single domain. A counter-action selector produces governance-policy-defined graduated counter-action, and a lineage recorder records each inference, classification, counter-action selection, and downstream consequence. The disclosure is independent of the specific physical actuation modality and the specific sensor stack.
The mechanism is applicable across operator-controlled platforms with hostility-relevant attributes, including road vehicles, vessels, aircraft, unmanned systems, industrial equipment, medical practitioners, and personal-agent-carried operators. The detected adversarial signatures span civilian-vehicular, unmanned-aerial, maritime, aircraft, robotic and industrial, pedestrian and personal-agent, cyber-physical, and defense-domain categories, along with composite multi-domain signatures, and each counter-action is constrained by governance-policy-defined authority, jurisdictional, laws-of-armed-conflict, civilian-safety, due-process, and use-of-force parameters per domain.
Each counter-action is admissibility-evaluated against the composite framework of Chapter 4 and lineage-recorded, supporting command audit, after-action review, legal review, and regulatory-compliance review. This article describes subject matter disclosed in U.S. Provisional Application No. 64/049,409.
