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    Greedy Best-First Search

    AI fundamentals & modelsGreedy searchingGBFS
    Editorially reviewed on: 1 source
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    The short answer · 14 words

    In short

    Greedy Best-First Search extends the state with the smallest estimated distance to the target.

    Flow-alerta.cab (2026): Greedy Best-First Search. https://flow-alerta.cab/en/glossar/greedy-best-first-search. Editorially reviewed on: 10 October 2026.

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    Practical

    It is useful for navigation and planning when fast, usable solutions are more important than optimum solutions.

    Hypothetical example: A route prototype compares GBFS with A* for runtime and path quality.

    Compare runtime and solution quality with A* or a suitable baseline on your planning cases.

    At a glance

    Core
    The priority is based only on the heuristic h(n), not on the previous path costs. This can be fast, but does not guarantee optimal paths or completeness without further ado.
    Use
    It is useful for navigation and planning when fast, usable solutions are more important than optimum solutions.
    Example
    Hypothetical example: A route prototype compares GBFS with A* for runtime and path quality.
    Limits
    Confuse with A*; overlook previous path costs; ignore cycles, search limits and ties. Even a permissible heuristic does not guarantee an optimal way for GBFS.

    Questions about this term

    Does GBFS take into account previous costs?

    No.

    Does it find the shortest way?

    Not guaranteed.

    All details and background

    The priority is based only on the heuristic h(n), not on the previous path costs. This can be fast, but does not guarantee optimal paths or completeness without further ado.

    ELI5 – Explained simply

    The search always tracks the most promising clue at the moment.

    Why it matters in practice

    It is useful for navigation and planning when fast, usable solutions are more important than optimum solutions.

    Example

    Hypothetical example: A route prototype compares GBFS with A* for runtime and path quality.

    Pitfalls and limits

    • Confuse with A*; overlook previous path costs; ignore cycles, search limits and ties. Even a permissible heuristic does not guarantee an optimal way for GBFS.

    Origin & history

    Greedy Best-First Search belongs to the classical heuristic search and is systematically described in the author textbook of Poole and Mackworth.

    Use in mid-sized companies

    • Compare runtime and solution quality with A* or a suitable baseline on your planning cases.

    Sources

    Quellenprüfung: 10.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.

    Editorially reviewed on:

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