Autonomous system

As explained in Delivering Machine Learning Projects: From design to deployment

An autonomous system is a system that operates independently for extended periods without human intervention and manages its own operational episodes.

An autonomous system operates unsupervised and independently for extended periods without human intervention, managing complete operational episodes itself. Increasing autonomy reduces opportunities for human control and raises assurance, engineering, transparency, documentation, and performance requirements. section 9.2.3 section 9.2

Treat autonomy as a production and governance decision:

• Choose deliberately among assistive, delegative, and autonomous system types because their functional and nonfunctional requirements differ. section 9.11
• Build stronger reliability assurance, system engineering, decision explanations, development records, monitoring, controls, testing, and ethical review as human intervention decreases. section 9.11 section 9.2
• Plan for operational support after release because users may be unable to intervene when an autonomous system fails. section 9.11 section 9.2

Self-driving car

A self-driving car manages the journey from origin to destination after the user selects the destination, while the development and selling team bears moral and ethical responsibility for resulting accidents. section 9.2.3

Figure 9.3 The control flow for a delegative remote control rover [1]

Use the rover control-flow figure to contrast delegative autonomy, where humans review and approve episodes, with fully autonomous operation. section 9.2.2

How Delivering Machine Learning Projects: From design to deployment covers it

How deep it goes

Defines unsupervised operation and explains assurance, transparency, documentation, and performance consequences, without detailing autonomy algorithms.

Examples

Uses self-driving cars, social-network recommendation systems, and the Perseverance rover to contrast autonomous and human-approved operation.

What you can do after

Evaluate autonomy choices and specify the assurance, controls, testing, monitoring, and governance needed before production release.

How it connects

Connects autonomous systems to assistive systems, delegative systems, human control, system engineering, machine learning, and ethical responsibility.

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Also explained in

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  Acing the CCNA Exam: Volume 1 Fundamentals and ProtocolsAn autonomous system is a collection of networks and routers under a common administrative control that participates in interdomain routing.

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Related concepts

• data streamproduces · A data stream is an ordered sequence of data items or events made available incrementally for consumption or processing.
• assistive systemcontrasts with · An assistive system is a human-facing computational system that provides information, advice, predictions, or recommendations without controlling the resulting decisions.
• delegative systemcontrasts with · A delegative system is a system that makes decisions on a user's behalf while providing the human with timely mechanisms to review, correct, or override those decisions.
• nonfunctional requirementuses · A nonfunctional requirement specifies a quality attribute, constraint, or operating condition that a system must satisfy beyond the particular functions it performs.
• automationcontrasts with · Automation is the execution of tasks or processes by machines or software with reduced direct human intervention.
• exterior gateway protocolused by · An exterior gateway protocol is a routing protocol that exchanges routing information between different autonomous systems.

This explainer was generated by Manning's knowledge graph from the text of Delivering Machine Learning Projects: From design to deployment. The section links point to the parts of the book it draws on.