Landmark-based Representation

Landmark-Based Representation is a spatial representation method that orients an agent within an environment by encoding positions relative to salient, identifiable objects or features, distinguishing it from grid- or path-integration-based approaches through its reliance on fixed, recognizable cues for localization and navigation.

211

Publications

13.9K

Citations

630

Authors

266

Institutions

Publications per year

2017–2026

56

Authors

630

  1. ML
    Marcia L. Spetch

    University of Alberta, Canada

    10 publications · 574 citations

    10

    h-index

  2. KC
    Ken Cheng

    Macquarie University, Australia

    8 publications · 529 citations

    8

    h-index

  3. RW
    Rüdiger Wehner

    University of Zurich, Switzerland

    6 publications · 976 citations

    6

    h-index

  4. YH
    Yi Hou

    National University of Defense Technology, China

    3 publications · 60 citations

    3

    h-index

  5. LK
    Lars Kuchinke

    Ruhr University Bochum, Germany

    3 publications · 53 citations

    3

    h-index

1–5 of 630

Venues

  1. Journal of comparative psychology

    7 publications · 651 citations

    7

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  2. Journal of Experimental Biology

    6 publications · 882 citations

    6

    h-index

  3. 5

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 593 citations

    4

    h-index

  5. Animal Learning & Behavior

    4 publications · 171 citations

    4

    h-index

1–5