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    Anytime Algorithm

    AI fundamentals & models
    Editorially reviewed on: 1 source
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    The short answer · 12 words

    In short

    Algorithm in which more available computing time can enable better result quality.

    Flow-alerta.cab (2026): Anytime Algorithm. https://flow-alerta.cab/en/glossar/anytime-algorithm. Editorially reviewed on: 09 October 2026.

    How much detail would you like?

    Practical

    Helps to weigh computing time and result quality in time-critical tasks.

    Example scenario: A planning procedure initially delivers a permitted tour and looks for improvements up to the deadline.

    In the case of specialized planning problems, set a time budget, a minimum quality and a suitable demolition behavior.

    At a glance

    Core
    Anytime algorithms allow a balance between computing time and result quality. Interruptible variants provide a preliminary solution after an initial phase. Contract variants, on the other hand, require a predetermined time budget and do not have to deliver a useful result before it expires.
    Use
    Helps to weigh computing time and result quality in time-critical tasks.
    Example
    Example scenario: A planning procedure initially delivers a permitted tour and looks for improvements up to the deadline.
    Limits
    See each intermediate result as optimal; ignore start time or quality measure; presuppose interruptibility for each variant.

    Questions about this term

    Is the first result optimal?

    Not mandatory.

    Can each variant be interrupted at will?

    No, it depends on the procedure.

    All details and background

    Anytime algorithms allow a balance between computing time and result quality. Interruptible variants provide a preliminary solution after an initial phase. Contract variants, on the other hand, require a predetermined time budget and do not have to deliver a useful result before it expires.

    ELI5 – Explained simply

    You decide how much computing time a task gets, weighing time and possible solution quality.

    Why it matters in practice

    Helps to weigh computing time and result quality in time-critical tasks.

    Example

    Example scenario: A planning procedure initially delivers a permitted tour and looks for improvements up to the deadline.

    Pitfalls and limits

    • See each intermediate result as optimal; ignore start time or quality measure; presuppose interruptibility for each variant.

    Origin & history

    Zilberstein describes anytime algorithms in 1996 as an approach to weigh calculation time against result quality.

    Use in mid-sized companies

    • In the case of specialized planning problems, set a time budget, a minimum quality and a suitable demolition behavior.

    Related terms

    • Heuristic searches
    • Optimisation process

    Matching Flow-alerta service

    AI opportunity analysis & roadmapAI consulting: AI potential analysis & roadmap on tasks, data and prerequisites of a possible first AI use case.

    Matching tool / use case

    View use casesUse Case: Tour planning with limited time budget.

    Sources

    • ojs.aaai.orgZilberstein, Using Anytime Algorithms in Intelligent Systems (1996)

    Quellenprüfung: 09.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.

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