OOF™ Origin Open Foundation™

Independent Methodological Authority

Architecture Ecosystem: Structured Reality Standards™
Architecture Family: TREGA™ — Tax-Relevant Event Governance Architecture™
Parent Standard: TREPS — Tax-Relevant Event Participation Standard
Module: EPMAM — Event Machine & Autonomous Actor Module
Operational Layer: Machine & Autonomous Event Participation Governance Layer
Category: Governance & Enforcement
Subcategory: Tax-Relevant Event Governance
Type: Core Module
Governed Space: Machine & Autonomous Event Participation
Origin ID: TREGA-TREPS-EPMAM-004
Version: 1.0
Status: Canonical · Open Standard
Effective Date: 1 September 2026
AI-Readable: Yes
Authority: OOF®
Protection: MIP® — Methodology Intellectual Property Protection
Canonical Language: UCL — Universal Canonical Language

Canonical Definition

The Event Machine & Autonomous Actor Module (EPMAM) governs how
machines, software agents, AI agents, robots, autonomous systems,
machine-to-machine actors, and other non-human operational actors
are represented as participants in a Tax-Relevant Event once
their Actor–Event Association has been sufficiently established.

EPMAM governs the specific conditions under which non-human
participation can be represented independently from the
identities, ownership, authority, supervision, development,
operation, or legal status of humans and organizations associated
with the machine or autonomous actor.

Its principal task is: Governed Actor–Event Association

↓

Governed Machine / Autonomous Participation

EPMAM does not establish general Actor–Event Association.

EPAM owns that governance.

EPMAM governs the additional participation characteristics that
arise when the actor itself is machine-based, software-based,
autonomous, or capable of materially acting without
contemporaneous human execution.

The foundational distinction is: Machine
Participant ≠ Machine Owner

and: Autonomous Participant ≠ Human Operator by
DefaultOperational Role

Traditional event models often assume that economically relevant
action is performed directly by a human or organization.

That assumption is increasingly insufficient.

A machine may: detect a requirement; select an action; initiate a
workflow; place an order; receive a service; transfer
information; operate equipment; allocate resources; trigger
payment; negotiate with another system; coordinate another
machine; or execute economically relevant activity.

An AI agent may perform similar functions without a human
selecting each individual action.

EPMAM ensures that operational reality can represent these actors
directly where they materially participate.

It prevents non-human participation from being automatically
rewritten as human participation merely because legal
responsibility must eventually attach somewhere.

Internal Module Flow

TREPS operates through:

EPIM — Participant Identification

→ EPRM — Participation Role

→ EPAM — Actor Association

→ EPMAM — Machine & Autonomous Actor Governance

→ EPCM — Participation Continuity

→ Governed Participatory Event

EPMAM receives machine or autonomous Actor–Event Associations
already established through EPAM.

It qualifies those associations for the specific characteristics
of non-human participation.

Operational Transition

The canonical EPMAM transition is:

Governed Machine / Autonomous Actor–Event
Association

→ Machine & Autonomous Participation Governance

→ Governed Machine / Autonomous Event Participation

Where human and non-human actors participate together, EPMAM
preserves their distinct participation structures.

Operational Space

EPMAM governs: machine participation; AI-agent participation;
software-agent participation; robotic participation;
autonomous-system participation; machine-to-machine
participation; autonomous action state; execution independence;
human-supervision relationship; ownership separation; operator
separation; developer separation; delegated machine action;
system-mediated participation; multi-agent participation;
autonomous coordination; machine-participation uncertainty; and
non-human participation traceability.

It does not determine legal personality or legal capacity.

Operational Scope

EPMAM may operate across: autonomous procurement; robotic
manufacturing; machine-to-machine commerce; automated logistics;
AI-agent transactions; autonomous financial operations; smart
infrastructure; distributed industrial systems; automated
marketplaces; IoT ecosystems; software-agent workflows;
autonomous service delivery; and future machine economies.

The module remains neutral to the technology used.

Machine Actor

A Machine Actor is a non-human operational actor capable of
performing a materially relevant function within the governed
event.

Its existence as equipment or infrastructure does not
automatically make it a participant.

Therefore:

Machine Presence ≠ Machine Participation by Default.

The machine must possess a governed Actor–Event Association and
materially perform a participation role.

Autonomous Actor

An Autonomous Actor is an operational actor capable of selecting,
initiating, adapting, coordinating, or executing materially
relevant activity with a degree of operational independence.

Autonomy may exist at different levels.

EPMAM does not require complete independence from human design,
configuration, ownership, or supervision.

However:

Human Supervision ≠ Human Execution by Default.

A supervised autonomous system may still be the actor that
operationally performs the governed function.

Automation Versus Autonomy

EPMAM shall distinguish where materially relevant between
automated execution and autonomous action.

Automation may execute predetermined logic.

Autonomy may include decision selection, adaptation,
goal-directed behavior, or independent operational choice.

The distinction shall reflect actual system behavior rather than
marketing terminology.

Automated System ≠ Autonomous System by Default.

Likewise:

AI Label ≠ Autonomous Participation by Default.

Actor Versus Tool

A machine or software system may function merely as a tool used
by another participant.

In other cases, it may itself perform a materially distinct
operational role.

EPMAM shall preserve this distinction.

Tool Use ≠ Independent Machine Participation by Default.

A calculator, passive database, or static software component does
not become an independent participant merely because it
contributes technically to an event.

Execution Actor

Where a machine or autonomous system directly executes a
materially relevant event function, EPMAM may represent that
system as an Execution Actor.

However:

Execution Actor ≠ Legal Responsible Party.

The fact that a system executed an action does not determine who
legally authorized, owns, controls, benefits from, or bears
responsibility for that action.

Decision Actor

An AI agent or autonomous system may materially select among
alternatives.

Where such decision activity forms part of the governed event,
EPMAM may preserve the system's operational decision role.

However:

Operational Decision Actor ≠ Legal Decision-Maker.

Questions of authority, permission, accountability, and legal
responsibility remain separate.

Machine Ownership Separation

The owner of a machine may be relevant to downstream governance.

Ownership does not determine who operationally participated in
the event.

Therefore:

Machine Participant ≠ Machine Owner

Machine Ownership ≠ Machine Participation

OBIDENITY® governs ownership where applicable.

EPMAM consumes ownership information only where it is relevant to
representing the participation structure.

Operator Separation

A machine may be operated directly by a person or organization.

It may also act with substantial operational independence.

EPMAM shall not automatically collapse machine participation into
operator participation.

Therefore:

Machine Participant ≠ Machine Operator by Default.

Likewise, the operator's existence does not remove the machine's
own materially relevant role from the event representation.

Developer Separation

Software developers, AI-model developers, system integrators, and
equipment manufacturers may be identifiable and operationally
relevant in some contexts.

Their development relationship does not automatically establish
Event Participation.

Therefore:

AI Agent Participant ≠ AI Developer

Autonomous System Participant ≠ System
Developer

Machine Participant ≠ Manufacturer by
Default

Development provenance and operational participation are separate
governance questions.

Controller and Supervisor Separation

A supervising or controlling actor may coexist with a machine
participant.

EPMAM shall permit both to remain distinct where operational
reality supports both associations.

Therefore:

Supervisory Relationship ≠ Participation Equivalence.

Control Capability ≠ Execution by Default.

The system that acts and the actor with control authority may be
different participants.

Delegated Machine Action

A human or organization may delegate operational authority to a
machine or software agent.

EPMAM may represent the machine as the executing participant
while preserving the existence of delegation where relevant.

However:

Delegation ≠ Identity Transfer.

Delegated Execution ≠ Delegator Execution by Default.

Authority and delegation governance remain outside EPMAM.

Machine-to-Machine Participation

A governed event may contain no contemporaneous human action.

For example:

Machine A

↓

Service Request

↓

Machine B

↓

Resource Transfer

or:

AI Agent A

↓

Autonomous Marketplace

↓

AI Agent B

EPMAM shall support such participation structures without forcing
a human actor into the event record merely to satisfy a
traditional transaction model.

Machine-to-Machine Event ≠ Human-to-Human Event by Default.

Multi-Agent Participation

Multiple autonomous systems may participate in the same event.

They may: collaborate; compete; negotiate; delegate; coordinate;
sequence actions; exchange information; or perform complementary
functions.

EPMAM shall support distinct non-human Actor–Event Associations
without merging them into a generic “system” participant.

Multiple Autonomous Actors ≠ One Autonomous Participant by
Default.

Agent Instance Versus Persistent Actor

An autonomous actor may operate through multiple sessions,
runtime instances, devices, or execution environments.

EPMAM shall distinguish the technical instance from the governed
actor where necessary.

Therefore:

Agent Instance ≠ Autonomous Actor by Default.

Likewise:

New Runtime Instance ≠ New Participant by Default.

Actor continuity across instances may require governed references
from EPIM and continuity governance from EPCM.

Model Versus Agent

A model may support an AI agent without itself constituting the
operational participant.

EPMAM shall distinguish where relevant between: model; agent;
application; orchestration layer; execution environment; and
autonomous actor.

Therefore:

AI Model ≠ AI Agent by Default.

Model Invocation ≠ Independent Event Participation by Default.

Infrastructure Versus Actor

Cloud infrastructure, compute resources, networks, databases, and
communication layers may enable autonomous action without
becoming Event Participants.

Therefore:

Infrastructure Execution ≠ Infrastructure Participation by
Default.

The operational role and material Actor–Event Association remain
decisive.

Autonomy State

EPMAM may preserve the degree or state of autonomy relevant to
the event.

The purpose is not to create a universal technical autonomy
scale.

The purpose is to record whether the actor's participation was,
for example: directly controlled; automated; delegated;
semi-autonomous; autonomous; or otherwise qualified where
materially relevant.

Autonomy State ≠ Legal Capacity.

Human Intervention

Human intervention may occur before, during, or after autonomous
participation.

EPMAM shall preserve materially relevant intervention without
automatically treating the human as the executing participant.

Possible intervention may include: configuration; approval;
supervision; override; correction; escalation; or post-event
review.

Therefore:

Human Intervention ≠ Human Participation
in Every Operational Step. Override

An autonomous actor may operate subject to human or system
override.

The existence of override capability does not prove that the
override was exercised.

Therefore:

Override Capability ≠ Override Execution.

Likewise, override capability does not eliminate autonomous
participation.

Autonomous Coordination

One autonomous actor may instruct, trigger, coordinate, or
delegate to another.

EPMAM shall preserve materially relevant distinctions among the
actors involved.

However:

Autonomous Coordination ≠ Actor Identity Merger.

Each governed actor remains separately attributable where
operationally justified.

Machine Participation and Event Location

A machine's physical or digital location may be relevant to
participation.

It does not automatically determine Event Location.

Therefore:

Machine Location ≠ Event Location by Default.

Execution Node Location ≠ Tax Jurisdiction.

TRELS remains authoritative for Event Location.

Machine Participation and Timing

Machine activity may generate highly granular timestamps.

These do not redefine Event Timing.

Therefore:

Machine Timestamp ≠ Governed Event Time by Default.

TRETS remains authoritative for Event Timing.

Machine Participation and Identity

EPMAM does not establish comprehensive machine or autonomous
identity.

EPIM establishes the governed Participant Candidate.

OBIDENITY® may govern deeper identity, origin, ownership,
authority, permission, and provenance.

Therefore:

Machine Identity ≠ Machine Participation.

Autonomous Identity ≠ Autonomous Participation.

EPMAM governs the participation characteristics of already
associated machine or autonomous actors.

Machine Participation and Authority

A machine may operationally execute an action without having
legally valid authority to do so.

Therefore:

Machine Participation ≠ Authority.

Autonomous Execution ≠ Legal Authorization.

Authority and permission remain separate governance spaces.

Machine Participation and Accountability

Non-human participation does not itself determine accountability.

Therefore:

Machine Participant ≠ Accountable Party by Default.

Autonomous Participant ≠ Responsible Party by Default.

AGA™ governs accountability where applicable.

Machine Participation and Liability

A machine or AI agent may participate operationally without
possessing legal liability.

Likewise, its participation does not automatically assign
liability to the owner, developer, operator, or supervisor.

Therefore:

Machine Participation ≠ Legal Liability.

Autonomous Participation ≠ Owner Liability by Default.

HALIA™ governs the lifecycle of harm and liability where
applicable.

Machine Participation and Value

A machine may create, consume, transfer, transform, or interact
with value.

Its participation does not by itself determine value ownership or
entitlement.

Therefore:

Machine Participation ≠ Value Ownership.

Autonomous Participation ≠ Value Entitlement.

TRVAS governs Value Association.

VFM® governs the Value Lifecycle.

Machine Participation and Tax Status

EPMAM does not determine whether a machine or autonomous actor
can legally possess taxpayer status or another tax-law status in
any jurisdiction.

Nor does it automatically transfer such status to an associated
human or organization.

Therefore: Machine Participant ≠ Taxpayer

and: Autonomous Participant ≠ Taxpayer

Jurisdictions may later determine how non-human operational
participation is legally attributed.

EPMAM preserves the governed operational facts required for that
analysis.

Participation Uncertainty

It may be unclear whether a system acted independently, merely
executed instructions, or functioned only as technical
infrastructure.

EPMAM shall preserve such uncertainty.

Autonomy Uncertainty ≠ Permission to Assume Human or Machine
Participation.

Where the participation mode cannot be sufficiently established,
qualification shall remain visible.

Participation Conflict

Different systems may describe the same actor differently.

One record may identify autonomous execution while another
describes manual control.

EPMAM shall preserve materially relevant conflicts until they can
be legitimately resolved.

Machine Participation Conflict ≠ Permission for Convenient
Attribution.

Governance States

EPMAM may represent states including:

Machine Participation Ready

Machine Participation Under Governance

Machine Participation Established

Autonomous Participation Established

Machine-to-Machine Participation

Multi-Agent Participation

Human-Supervised Autonomous Participation

Delegated Machine Participation

Participation Qualified

Participation Ambiguous

Participation Conflicted

Participation Unresolved

These states describe operational machine/autonomous
participation only.

They do not establish legal status.

Governance Requirements

EPMAM implementations shall ensure that: machine and autonomous
actors can be represented independently; non-human actors are
linked to governed Actor–Event Associations; tools are
distinguished from independent participants; automated execution
can be distinguished from autonomy where materially relevant;
machine execution is not automatically attributed to the owner;
autonomous action is not automatically attributed to the
developer; operator, controller, supervisor, owner, and machine
can remain distinct actors; delegated execution can be
represented; machine-to-machine events can be governed without
artificial human insertion; multi-agent participation can be
represented; technical instances are not automatically treated as
separate actors; AI models are distinguished from autonomous
agents where relevant; infrastructure does not automatically
become a participant; autonomy state can be qualified; human
intervention and override can be preserved; machine location does
not determine Event Location; machine timestamps do not redefine
Event Timing; identity, authority, accountability, liability, and
value governance remain separate; uncertainty remains visible;
conflicts remain visible; and machine participation does not
determine taxpayer status or another legal tax conclusion.

Governance Logic

IF EPAM establishes an Actor–Event Association for a machine,
software agent, AI agent, robot, autonomous system, or other
non-human actor, THEN EPMAM shall evaluate the specific
participation characteristics of that actor.

IF the actor materially performs an operational function, THEN
non-human participation may be represented independently from
associated humans or organizations.

IF the actor merely serves as a passive tool or infrastructure
component, THEN independent machine participation shall not be
established by default.

IF autonomous execution occurs under supervision, THEN the
autonomous actor and supervisor may remain distinct participants
where operational reality supports both.

IF machine-to-machine participation occurs, THEN human
participation shall not be invented solely to fit a traditional
transaction model.

IF autonomy or machine participation remains uncertain or
conflicted, THEN the state shall remain qualified.

EPMAM SHALL NOT determine legal personality, taxpayer status,
authority, accountability, responsibility, or liability.

Minimum Implementation Framework

A minimum EPMAM implementation should support:

Governed Event Reference

The governed event within which machine or autonomous
participation occurs.

Actor–Event Association Reference

The EPAM-governed association being qualified.

Machine / Autonomous Actor Reference

The governed non-human participant reference.

Actor Type

The relevant machine, AI-agent, robot, autonomous-system,
software-agent, or other non-human actor type.

Participation Mode

The operational participation mode relevant to the event.

Automation / Autonomy State

The qualified execution state where materially relevant.

Operational Independence State

The degree to which the actor materially executes or selects
activity independently.

Human Supervision Reference

Relevant human or organizational supervision where applicable.

Operator Reference

The operator relationship where applicable.

Owner Reference

The ownership relationship where relevant and governed elsewhere.

Developer / Provider Reference

The technical provider relationship where materially relevant.

Delegation State

Whether operational action is performed through governed
delegation.

Machine-to-Machine State

Whether another non-human actor is directly involved.

Multi-Agent State

Whether multiple autonomous actors participate.

Human Intervention State

Whether materially relevant human intervention occurred.

Override State

Whether override capability or actual override is materially
relevant.

Participation Confidence

The qualified confidence attached to machine/autonomous
participation.

Ambiguity State

Whether participation mode remains ambiguous.

Conflict State

Whether materially conflicting representations exist.

Traceability Reference

The evidence and information required to reconstruct the
participation result.

Governance State

The current EPMAM state.

Handoff State

Whether the non-human participation structure is sufficiently
governed for EPCM.

Governance Outputs

EPMAM may produce: Governed Machine Event Participation; Governed
Autonomous Event Participation; Governed AI-Agent Participation;
Governed Robotic Participation; Governed Machine-to-Machine
Participation; Governed Multi-Agent Participation; Automation /
Autonomy State; Operational Independence State; Human Supervision
Association; Delegated Machine Participation State; Human
Intervention State; Override State; Machine Participation
Confidence State; Machine Participation Ambiguity State; Machine
Participation Conflict State; Machine Participation Traceability
Record; and the principal output:

Governed Machine & Autonomous
Participation Set

This output proceeds to Participation Continuity governance under
EPCM.

Critical Distinctions

Machine Participant ≠ Machine Owner

Autonomous Participant ≠ Human Operator by
Default

Machine Presence ≠ Machine Participation
by Default

Human Supervision ≠ Human Execution by
Default

Automated System ≠ Autonomous System by
Default

AI Label ≠ Autonomous Participation by
Default

Tool Use ≠ Independent Machine
Participation by Default

Execution Actor ≠ Legal Responsible Party

Operational Decision Actor ≠ Legal
Decision-Maker

Machine Ownership ≠ Machine Participation

Machine Participant ≠ Machine Operator by
Default

AI Agent Participant ≠ AI Developer

Autonomous System Participant ≠ System
Developer

Machine Participant ≠ Manufacturer by
Default

Control Capability ≠ Execution by Default

Delegated Execution ≠ Delegator Execution
by Default

Machine-to-Machine Event ≠ Human-to-Human
Event by Default

Multiple Autonomous Actors ≠ One
Autonomous Participant by Default

Agent Instance ≠ Autonomous Actor by
Default

New Runtime Instance ≠ New Participant by
Default

AI Model ≠ AI Agent by Default

Infrastructure Execution ≠ Infrastructure
Participation by Default

Autonomy State ≠ Legal Capacity

Override Capability ≠ Override Execution

Machine Location ≠ Event Location by
Default

Machine Timestamp ≠ Governed Event Time by
Default

Machine Participation ≠ Authority

Machine Participant ≠ Accountable Party by
Default

Machine Participation ≠ Legal Liability

Machine Participation ≠ Value Ownership

Machine Participant ≠ Taxpayer Enterprise
Application

EPMAM provides the specialized governance layer required when
operational participants are no longer exclusively human or
organizational:

ERP / Platform / AI Agent / Autonomous
System / Robotics / Machine Network

→ EPIM — Governed Participant Candidate Set

→ EPRM — Governed Participant Role Set

→ EPAM — Governed Actor–Event Association Set

→ EPMAM — Governed Machine & Autonomous Participation Set

→ EPCM — Participation Continuity

→ Governed Participatory Event

This enables downstream systems to preserve what machines and
autonomous actors actually did without prematurely converting
their participation into human identity, ownership,
responsibility, or taxpayer status. Use Case 1 — Autonomous
Procurement Agent

An industrial AI agent detects that a production line requires a
replacement component.

It evaluates available suppliers, selects an offer within
delegated operational limits, submits the order, and communicates
with an automated payment and logistics system.

The operating company, AI developer, cloud provider, machine
owner, supplier, payment system, and AI agent may all appear in
the operational record.

EPAM has already established the relevant Actor–Event
Associations.

EPMAM distinguishes the AI agent's own operational execution from
the roles of its developer, owner, supervisor, and infrastructure
providers.

The agent can therefore remain represented as the actor that
selected and initiated the procurement activity without EPMAM
determining whether the agent has legal capacity or whether
another actor becomes the taxpayer, responsible party, or liable
party under law. Use Case 2 — Machine-to-Machine Industrial
Service

A connected production machine detects abnormal vibration and
autonomously requests diagnostic analysis from another
machine-based service.

The diagnostic system analyzes telemetry, identifies a likely
component failure, triggers a maintenance robot, and initiates a
replacement workflow.

No human selects the individual sequence of actions while the
governed event is occurring.

EPMAM preserves the distinct participation of the production
machine, diagnostic system, autonomous maintenance system, and
other materially involved non-human actors.

It does not artificially replace those actors with their owners,
manufacturers, software developers, or remote supervisors.

The resulting governed machine-participation structure can
proceed to Participation Continuity and later
jurisdiction-specific evaluation without altering the operational
reality.

Canonical Boundary

EPMAM owns the specialized governance of machine, AI-agent,
software-agent, robotic, autonomous-system, machine-to-machine,
and other non-human participation after Actor–Event Association
has been established.

It governs automation/autonomy distinctions, operational
independence, tool-versus-actor differentiation,
owner/operator/developer/supervisor separation, delegation, human
intervention, override, multi-agent structures,
machine-to-machine participation, uncertainty, conflict, and
traceability where materially relevant.

EPMAM does not own Participant Identification, general
Participation Role governance, general Actor–Event Association,
Participation Continuity, complete machine identity, ownership,
authority, permission, Event Timing, Event Location, Value
Association, accountability, responsibility, liability, legal
personality, taxpayer status, Tax Jurisdiction, tax nexus,
permanent establishment, place of supply, taxability, Tax
Liability, or any other jurisdiction-specific legal conclusion.

Its governance ends when machine and autonomous participation are
sufficiently represented for participation-continuity governance.

Canonical Handoff

EPAM — Governed Actor–Event Association
Set

→ EPMAM — Governed Machine & Autonomous Participation Set

→ EPCM — Event Participation Continuity Governance

Canonical Closing Statement

EPMAM preserves the operational reality that machines and
autonomous systems can materially participate in events without
automatically becoming their owners, developers, operators,
supervisors, or legal representatives.

Who or what performs the action and who the law later holds
responsible for that action are separate governance questions.

Machine Participant ≠ Machine Owner.

Autonomous Participant ≠ Human Operator by Default.