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13 · Cognition & Control

AGOW
in GenOS.

An active workspace where candidate frames compete and selected content can be broadcast under policy.

IMPLEMENTATIONPartial
RUNTIME INTEGRATIONWired
EVIDENCEIntegration tested
LAST REVIEWED SOURCEGenOS 5091f70 ↗

AGOW has persisted workspace, arbitration, query and broadcast paths. The current AGOW suite, including production-wiring checks, passed; this does not establish cognitive or consciousness equivalence.

Documentation markers describe linked material, not verified GenOS behavior. Simulation and benchmark flags remain partial until a concept-specific artifact is linked.

DOCUMENTATION
  • Science
  • Mathematics
  • Interactive model
  • Mechanism steps
  • Benchmark
  • FR explanation
DEFINITION AND SCIENCE

What it means
in GenOS.

IN ONE SENTENCE

An active workspace where candidate frames compete and selected content can be broadcast under policy.

BIOLOGICAL / SCIENTIFIC BASIS

AGOW is a software workspace in which candidate representations may be evaluated and selected under explicit policy. Neuronal threshold models provide historical context for formal abstractions, not evidence that AGOW reproduces brain-wide cognition.

BIOLOGICAL INSPIRATION · WHY THIS ANALOGY

Neural workspace theories study competition and broadcast among representations. AGOW borrows selection and broadcast as software design ideas, without a claim about consciousness.

GENOS TRANSLATION

An active workspace where candidate frames compete and selected content can be broadcast under policy.

MATHEMATICAL / LOGICAL MODEL

For candidate c, selection can be expressed as argmax_c U(c) subject to admissibility constraints A(c)=true and resource budget B(c)≤B_max. The objective and gates are policy inputs, not universal laws.

ANIMATED DIAGRAM · INTERACTIVE MODEL

Explore the mechanism: AGOW

A qualitative teaching model of this concept. It does not run GenOS or validate its implementation.

01 / 03
Current transition · Step 1Admit candidate frames

The modeled transition may proceed. Change the assumption and move through the stages to inspect the decision path.

PROCESS AND USE

How it works
at a glance.

01

Admit candidate frames

An active workspace where candidate frames compete and selected content can be broadcast under policy.

02

Compete for attention

For candidate c, selection can be expressed as argmax_c U(c) subject to admissibility constraints A(c)=true and resource budget B(c)≤B_max. The objective and gates are policy inputs, not universal laws.

03

Broadcast selected content

Broadcast selected content. AGOW is a software workspace in which candidate representations may be evaluated and selected under explicit policy. Neuronal threshold models provide historical context for formal abstractions, not evidence that AGOW reproduces brain-wide cognition.

RUNTIME IMPLEMENTATION

What is connected,
and how far.

The linked, versioned GenOS source defines this concept's supported operations and limits. The status axes describe the implementation and evidence recorded for this entry; they do not establish general mission success, scientific equivalence or behavior beyond that scope.

IMPLEMENTATION DETAIL

AGOW has persisted workspace, arbitration, query and broadcast paths. The current AGOW suite, including production-wiring checks, passed; this does not establish cognitive or consciousness equivalence.

FAILURE MODES

A threshold can suppress low-salience but critical evidence. · Correlated salience signals can reinforce a shared blind spot. · Broadcast is not proof or a claim of consciousness.

PRIMARY RESEARCH · MECHANISM LEVEL

The mechanism
behind the analogy.

THRESHOLD LOGIC NETWORKS · 1943

A logical calculus of the ideas immanent in nervous activity

Warren S. McCulloch and Walter Pitts · Bulletin of Mathematical Biophysics 5, 115–133

Formalizes idealized all-or-none units as logical networks; the abstraction is not a full biological neuron model.

Open publication ↗

Primary research describes the cited mechanism; specific technologies may instead cite their original technical documentation. These sources provide context and do not validate the GenOS implementation.

EVIDENCE AND LIMITS

Scope and validation boundaries

The linked, versioned GenOS source defines this concept's supported operations and limits. The status axes describe the implementation and evidence recorded for this entry; they do not establish general mission success, scientific equivalence or behavior beyond that scope.