Defined scope
- Perception
- Planning
- Action
- Feedback
- Human oversight
- Operational boundaries
CONCEPT
An autonomous system can perceive relevant state, select actions and adapt behavior toward objectives with limited direct human control during operation.
Autonomous systems combine sensing, models, planning, execution, feedback, constraints, governance and human intervention paths.
EDITORIAL FRAME
A concise view of its scope, position, limitations and supporting sources.
An autonomous system observes an environment, chooses actions and uses feedback to continue operation without a human specifying every step. Autonomy exists by degree and within a designed action space.
The system may include sensors, state estimation, models, planners, policies, tools, actuators, logs, safety constraints and human override. A language-model agent is one form; robots, adaptive control systems and simulation actors are others.
Autonomy should be connected to contextual execution. Identity, permissions, evidence, environment and reversible actions matter more than a broad claim that a system can “act alone.”
Real environments change, sensors fail, objectives conflict and errors compound. Autonomous systems require bounded authority, monitoring, incident response and clear responsibility for outcomes.
See NIST AI RMF, AI Agent, Cybernetic Feedback and Contextual Execution.
DOCUMENTED RELATIONSHIPS
Each link names the relationship between two entries and why it matters.
AI Agents vs AI Workflows distinguishes bounded agents from broader autonomous systems.
Contextual Execution and Graph Runtimes documents Autonomous System as one of its declared subjects.
Autonomous System is an explicit member of the Knowledge Hub Third Wave collection.
Autonomous System. 1.0.0. Electronic Artefacts, 2026-06-24. https://electronicartefacts.com/knowledge/concepts/autonomous-system/
3 public links connect this page to nearby projects, concepts and references.