Cited by 18Multi-Agent Systems and NegotiationExplainable Artificial Intelligence (XAI)Logic, Reasoning, and Knowledge

Representation, justification, and explanation in a value-driven agent: an argumentation-based approach

Open access
Liao, Beishui, Anderson, Michael, Anderson, Susan Leigh·2021·AI and Ethics

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s43681-020-00001-8

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

  • A series of works [13, 15, 16, 55, 61, 69] refer to justifications as ways of ensuring that a decision is good (in contrast to understanding a decision), which is in line with the definition proposed in this paper.

    “However, a series of works [13, 15, 16, 55, 61, 69], refer to justifications as ways of ensuring that a decision is good (in contrast to understanding a decision), which is in line with the definition proposed in this paper.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 35 · Cited by 18

Research works printed but not linked: 4

  1. Arkoudas, K., Bringsjord, S., Bello, P.: Toward ethical robots via mechanized deontic logic. In: AAAI fall symposium on machine ethics, pp. 17-23 (2005)
  2. Baroni, P., Gabbay, D., Giacomin, M., van der Torre, L. (eds.): Handbook of Formal Argumentation. College Publications, Lon- don (2018)
  3. Baum, K., Hermanns, H., Speith, T.: From machine ethics to machine explainability and back. In: International symposium on artificial intelligence and mathematics, ISAIM 2018, Fort Laud- erdale, Florida, USA, January 3-5, 2018 (2018). http://isaim 2018. cs.virgi nia.edu/paper s/ISAIM 2018_Ethic s_Baum_etal.pdf
  4. Liao, B.: Efficient Computation of Argumentation Semantics. Intelligent systems series. Academic Press, New York (2014)

Authors
Liao, B., Anderson, M., & Anderson, S. L.
Affiliations
  • Zhejiang University (CN)
  • University of Hartford (US)
  • University of Connecticut (US)
Corresponding author
Liao, Beishui
Venue
AI and Ethics
Published
2020-10-06
Volume
1
Issue
1
Pages
5-19
ISSN
  • 2730-5953 (ISSN-L)
  • 2730-5961
OpenAlex
W3085927132
Cited by
18
References
35
Citations by year
2026: 2 · 2024: 1 · 2023: 4 · 2022: 2 · 2021: 7 · 2020: 2
Type
journal article
Language
en
Open access
Locations
  • AI and Ethics (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • Natural Science Foundation of Zhejiang Province (LY20F030014)
  • Major Program of National Fund of Philosophy and Social Science of China (18ZDA290, 17ZDA026)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
  • Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
  • Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
Keywords
explainable AI, argumentation, assumption-based argumentation, justification of decisions, practical reasoning, epistemic reasoning

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 ›

Are you an author, or do you see a problem with this page? Request a review