Agent-based Generalization

Agent-Based Generalization is a cartographic generalization method in which autonomous computational agents, representing geographic features or map objects, iteratively perform localized generalization operations through rule-based behaviors and spatial interactions, thereby collectively achieving global map simplification while preserving spatial relationships and context-specific constraints.

21

Publications

725

Citations

65

Authors

29

Institutions

Publications per year

2017–2026

12

Authors

65

  1. JT
    Julian Togelius

    New York University, United States

    4 publications · 158 citations

    4

    h-index

  2. AK
    Ahmed Khalifa

    New York University, United States

    4 publications · 158 citations

    4

    h-index

  3. CD
    Cécile Duchêne

    Institut national de l’information géographique et forestière, France

    4 publications · 145 citations

    4

    h-index

  4. PB
    Philip Bontrager

    New York University, United States

    4 publications · 158 citations

    4

    h-index

  5. AR
    Anne Ruas

    Institut national de l’information géographique et forestière, France

    3 publications · 191 citations

    3

    h-index

1–5 of 65

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 207 citations

    5

    h-index

  2. American Journal of Infection Control

    AJIC · 1 publications · 30 citations

    1

    h-index

  3. Artificial Life

    1 publications · 17 citations

    1

    h-index

  4. Cognitive Science

    1 publications · 10 citations

    1

    h-index

  5. 1

    h-index

1–5