Cited by 3,227Reinforcement Learning in RoboticsRobot Manipulation and LearningSocial Robot Interaction and HRI

A survey of robot learning from demonstration

Argall, Brenna D., Chernova, Sonia, Veloso, Manuela, Browning, Brett·2009·Robotics and Autonomous Systems

Integrity signals

Registry

Crossref · 10.1016/j.robot.2008.10.024

Cites

114 of 114 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?

  • Design issues on data collection, pre-processing, cleaning, labeling and augmentation, including big data challenges, exist for ML applications.

    “-Data Design: Design issues on data collection, pre-processing, cleaning, labeling and augmentation, including big data challenges [17,23,25-27, 31,33,41,44,74-76,105,114-116].”
  • Model management in the deployment phase, including model validation, decisions on model retraining, adversarial settings, backwards compatibility of trained models, and governance issues, is a maintenance challenge.

    “-Model Management: Challenge topics on ML model management in the deployment phase, including model validation, decisions on model retraining, adversarial settings, and backwards compatibility of trained models.The governance issues in model management also fit within this category [27,34].”
  • There are challenges on ML model management and governance.

    “As mentioned in 4.5, there are challenges on ML model management and governance [18,27,34,65,88].”
  • Developing the skill set for ML applications is the major challenge related to the software engineering professional practice knowledge area.

    “Developing the skill set for ML applications is the major challenge related to this KA [15,16,27,32,39,40,59].”
  • The main challenges in group dynamics and psychology are collaboration to ensure a successful project and adequate communication with customers.

    “The main challenges in this category are collaboration to ensure a successful project and adequate communication with customers [17,18,21,27,40,59,83].”

Cites

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4 of the 118 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Argall, B. D., Chernova, S., Veloso, M., & Browning, B.
Affiliations
Carnegie Mellon University (US)
Corresponding author
Argall, Brenna D.
Venue
Robotics and Autonomous Systems
Publisher
Elsevier BV
Published
2009-05
Volume
57
Issue
5
Pages
469-483
ISSN
0921-8890 (ISSN-L)
OpenAlex
W1986014385
Cited by
3,227
References
118
Citations by year
2026: 107 · 2025: 154 · 2024: 152 · 2023: 199 · 2022: 205 · 2021: 286 · 2020: 304 · 2019: 341 · 2018: 256 · 2017: 216 · 2016: 191 · 2015: 204 · 2014: 162 · 2013: 160 · 2012: 117
FWCI
91.43
Type
journal article
Language
en
Open access
closed
Locations
Robotics and Autonomous Systems (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
  • Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
Keywords
imitation learning, robot learning, teleoperation, matching function, dynamics model

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.

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