Distributed Cognitive Network
Volume V
DCN Runtime Specification 0.1
Part 1
Cognitive Kernel, Runtime Architecture, and the Cognitive Execution Cycle
1. Purpose
This specification defines the runtime responsible for executing cognition inside a Mind.
Previous volumes define the architecture, K-Line Protocol, Actum Compute, and Actum cognition history. This volume specifies the local runtime that transforms goals, observations, memory, K-lines, experts, artifacts, policies, authority, and world state into coherent action.
2. Design Philosophy
Traditional operating systems schedule processes, threads, memory, files, and devices. The DCN Runtime schedules cognition.
The runtime manages attention, reasoning, experts, artifacts, memory, authority, learning, and execution. It is therefore a cognitive operating system rather than an agent framework.
3. The Cognitive Kernel
The Cognitive Kernel is the trusted control core of every Mind. It is intentionally small.
Its responsibilities are to maintain cognitive state, allocate attention, schedule cognition, activate K-lines, escalate to System 2, resolve capabilities, enforce authority boundaries, preserve world consistency, and coordinate learning.
The Cognitive Kernel SHOULD NOT attempt to solve arbitrary problems itself.
4. Runtime Architecture
The canonical runtime is:
DCN Runtime
Cognitive Kernel
│
┌────────────────────┼────────────────────┐
│ │ │
▼ ▼ ▼
System 1 System 2 World State
│ │ │
▼ ▼ ▼
K-lines Expert Network SurrealDB
│ │ │
└──────────────┬─────┴────────────────────┘
▼
Patch Proposal Engine
▼
Authority Validation
▼
State Commit
The runtime never mutates state directly through reasoning components.
5. Runtime Principles
The runtime SHALL preserve the following principles.
5.1 Local-first cognition
Whenever practical, cognition executes locally; memory, authority, and personal context remain local. Remote execution is an optimization, not a requirement.
5.2 Proposal-first execution
Reasoning never directly mutates the world:
think → propose → validate → authorize → commit
5.3 Attention is scarce
Computation, battery, money, latency, network capacity, and human attention are scarce resources requiring allocation.
5.4 Learning never stops
Every execution may become future cognition. Learning is continuous rather than a separate training phase.
6. Runtime State
The Cognitive Kernel maintains active goals and tasks, current context, working memory, attention and resource budgets, authority context, active K-lines, running experts, pending patches and evaluations, and background learning jobs.
This runtime state is distinct from persistent long-term memory.
7. The Cognitive Execution Cycle
Every request passes through the same high-level recursive cycle:
Observe
↓
Interpret
↓
Recognize
↓
Plan
↓
Execute
↓
Validate
↓
Learn
Subtasks execute their own cycles.
8. Observe
Observation gathers user input, sensors, world events, external messages, background changes, and completed jobs. Observation records; it does not establish interpretation or truth.
9. Interpret
Interpretation converts observations into semantic structures such as intent, entities, goals, constraints, risks, urgency, and context. Interpretation MAY use lightweight local models.
10. Recognize
Recognition asks whether the Mind has successfully solved a sufficiently similar problem before. It queries K-line triggers, semantic fingerprints, active plans, episodic memory, and current world state and produces candidate K-lines.
11. Plan
Planning decides whether System 1 is sufficient, System 2 is required, additional information is needed, authority is missing, or external capabilities are required. Planning does not itself commit side effects.
12. Execute
Execution activates artifacts, local experts, remote experts, MCP capabilities, A2A agents, or humans. Execution produces results and proposals rather than direct world mutation.
13. Validate
Validation checks policy, authority, consistency, expected outputs, evaluation requirements, and safety constraints. Validation determines whether proposals are eligible for commitment.
14. Learn
Learning records episodes, evaluations, failures, successes, novelty, and opportunities for compilation. Learning SHOULD be asynchronous whenever possible.
15. Cognitive Resources
The runtime schedules attention, latency, money, battery, memory, network capacity, human interruption, and expert availability. These resources are jointly optimized.
16. Attention
Attention is the Cognitive Kernel's primary scheduling primitive. It determines what is processed now, deferred, forgotten, or escalated. This concept is distinct from transformer attention.
17. Goals
Every execution occurs in service of one or more goals. Goals form a graph rather than a stack and may contain subgoals, dependencies, priorities, and constraints.
18. Working Memory
Working memory contains currently relevant facts, active K-lines and experts, intermediate outputs, and pending decisions. It is intentionally small and transient.
19. Long-Term Memory
Long-term memory includes the world model, episodic memory, K-lines, artifacts, trust views, evaluations, plans, preferences, and relationships. It is persistent.
20. Cognitive Stack
The runtime stack is:
Observation
↓
Interpretation
↓
Recognition
↓
Planning
↓
Execution
↓
Validation
↓
Learning
Every subsystem participates in one or more stages of this pipeline.
21. World State
The world model is authoritative for the Mind's current state. Cognitive components reason about the world; they do not independently own it. Cognition is grounded in current world state plus committed history.
22. Patch-Oriented Execution
Execution that proposes a state change produces a PatchProposal rather than directly mutating the world. A patch contains intended changes, justification, dependencies, required authority, and originating execution.
23. Runtime Events
The runtime is event-driven. Canonical events include ObservationReceived, GoalCreated, GoalCompleted, ContextChanged, KLineActivated, ExpertBound, ExecutionCompleted, EvaluationCompleted, PatchCommitted, ArtifactCompiled, and BackgroundLearningTriggered.
Runtime events are immutable records of runtime occurrence; durable network claims are represented separately through Actum Acts where required.
24. Runtime Loop
Conceptually:
event
↓
scheduler
↓
Cognitive Kernel
↓
appropriate subsystem
↓
new events
The runtime continuously reacts to relevant events.
25. Background Work
Compilation, evaluation, indexing, K-line discovery, artifact optimization, reputation updates, and synchronization SHOULD execute opportunistically when they do not need to block foreground cognition.
26. Local Autonomy
Every Mind remains autonomous. Decisions, trust, activation, and authority remain local even when the Mind participates in the wider DCN. The runtime MUST NOT assume continuous network connectivity.
27. Runtime Invariants
The DCN Runtime SHALL preserve these invariants:
- The Cognitive Kernel allocates cognition; it is not required to perform all cognition.
- World state is authoritative; reasoning proposes changes rather than mutating state directly.
- Working memory and long-term memory are distinct.
- Attention is a managed runtime resource.
- Learning is continuous.
- Every execution can become input to future cognition.
- Local autonomy is preserved within the federated network.
28. Strategic Thesis
Traditional operating systems manage computation. The DCN Runtime manages cognition.
The Cognitive Kernel schedules and protects cognitive execution while K-lines, experts, artifacts, Actum Compute, Actum, evidence systems, MCP, A2A, and other transports or execution technologies cooperate around it.
The Cognitive Kernel is intentionally minimal. Its purpose is not to be the smartest component; its purpose is to keep the Mind coherent, trustworthy, efficient, resource-aware, and continuously capable of learning.