Cited by 180Robotics and Automated SystemsRobot Manipulation and LearningReinforcement Learning in Robotics

Towards a science of integrated AI and Robotics

Open access
Rajan, Kanna, Saffiotti, Alessandro·2017·Artificial Intelligence

Integrity signals

Registry

Crossref · 10.1016/j.artint.2017.03.003

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Improved computational power of smaller form-factor devices has made it possible for them to run sophisticated algorithms.

    “First, owing to the rapid advancement in hardware, the improved computational power of smaller form-factor devices has made it possible for them to run sophisticated algorithms [3].”

Cites

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Authors
Rajan, K., & Saffiotti, A.
Affiliations
  • Universidade do Porto (PT)
  • Örebro University (SE)
Corresponding author
  • Rajan, Kanna
  • Saffiotti, Alessandro
Venue
Artificial Intelligence
Publisher
Elsevier BV
Published
2017-06
Volume
247
Pages
1-9
ISSN
0004-3702 (ISSN-L)
OpenAlex
W2603920273
Cited by
180
References
1
Citations by year
2026: 8 · 2025: 23 · 2024: 42 · 2023: 22 · 2022: 25 · 2021: 20 · 2020: 18 · 2019: 10 · 2018: 10 · 2017: 2
FWCI
6.87
Type
journal article
Language
en
Open access
Locations
  • Artificial Intelligence (publishedVersion)
  • KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
Funders
  • Office of Naval Research (N00014-14-1-0536)
  • Örebro Universitet (RV422/2011)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Robotics and Automated Systems
  • Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
  • Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
Keywords
embedded intelligence, autonomous systems, sensorimotor control, machine intelligence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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