Best-first Search

Best-First Search is a heuristic-driven graph traversal algorithm that belongs to the class of informed search strategies, distinguished by its selection of the most promising node for expansion based on an evaluation function that estimates the proximity to the goal.

301

Publications

17K

Citations

649

Authors

298

Institutions

Publications per year

2017–2026

68

Authors

649

  1. RE
    Richard E. Korf

    University of California, Los Angeles, United States

    14 publications · 750 citations

    12

    h-index

  2. RD
    Rina Dechter

    University of California, Irvine, United States

    8 publications · 1.2K citations

    8

    h-index

  3. WR
    Wheeler Ruml

    University of New Hampshire at Manchester, United States

    7 publications · 254 citations

    7

    h-index

  4. AK
    Akihiro Kishimoto

    University of Alberta, Canada

    5 publications · 173 citations

    5

    h-index

  5. HG
    Héctor Geffner

    Universitat Pompeu Fabra, Spain

    5 publications · 227 citations

    5

    h-index

1–5 of 649

Venues

  1. 13

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 14 publications · 348 citations

    11

    h-index

  3. 8

    h-index

  4. Journal of Artificial Intelligence Research

    JAIR · 7 publications · 415 citations

    7

    h-index

  5. National Conference on Artificial Intelligence

    Conference · 7 publications · 165 citations

    7

    h-index

1–5