Affordance Learning

Affordance Learning is a robotic learning framework that identifies and models the possible interactions between an agent and objects in its environment based on sensorimotor data, distinguishing itself by enabling action prediction and selection through perception of environmental affordances without requiring explicit supervision.

203

Publications

12.1K

Citations

544

Authors

231

Institutions

Publications per year

2017–2026

79

Authors

544

  1. EU
    Emre Uğur

    Boğaziçi University, Türkiye

    17 publications · 699 citations

    14

    h-index

  2. EŞ
    Erol Şahi̇n

    Middle East Technical University, Türkiye

    15 publications · 584 citations

    13

    h-index

  3. JP
    Justus Piater

    Universität Innsbruck, Austria

    10 publications · 402 citations

    10

    h-index

  4. JS
    José Santos-Victor

    Instituto Superior Técnico, Portugal

    9 publications · 650 citations

    9

    h-index

  5. AB
    Alexandre Bernardino

    Instituto Superior Técnico, Portugal

    8 publications · 561 citations

    8

    h-index

1–5 of 544

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 407 citations

    12

    h-index

  2. IEEE Transactions on Cognitive and Developmental Systems

    TCDS · 4 publications · 163 citations

    4

    h-index

  3. Adaptive Behavior

    4 publications · 269 citations

    4

    h-index

  4. Ecological Psychology

    3 publications · 183 citations

    3

    h-index

  5. 3

    h-index

1–5