The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Argumentation Schemes
Abstract
This book provides a systematic analysis of many common argumentation schemes and a compendium of 96 schemes. The study of these schemes, or forms of argument that capture stereotypical patterns of human reasoning, is at the core of argumentation research. Surveying all aspects of argumentation schemes from the ground up, the book takes the reader from the elementary exposition in the first chapter to the latest state of the art in the research efforts to formalize and classify the schemes, outlined in the last chapter. It provides a systematic and comprehensive account, with notation suitable for computational applications that increasingly make use of argumentation schemes.
Overview
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.
Integrity signals
Registry
Cites
Statistics
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Intelligent agents: theory and practice
Wooldridge, M., & Jennings, N. R. (1995) · The Knowledge Engineering Review · doi:10.1017/s0269888900008122 · Cited by 6,810
Cited by
A Framework for Conceptual Contributions in Marketing
MacInnis, D. J. (2011) · Journal of Marketing · doi:10.1509/jmkg.75.4.136 · Cited by 1,547
Liu, O. L., Frankel, L., & Roohr, K. C. (2014) · ETS Research Report Series · doi:10.1002/ets2.12009 · Cited by 340
Toward Artificial Argumentation
Atkinson, K., Baroni, P., Giacomin, M., Hunter, A., Prakken, H., Reed, C., Simari, G., Thimm, M., & Villata, S. (2017) · AI Magazine · doi:10.1609/aimag.v38i3.2704 · Cited by 142
Self-citationLogic-based technologies for multi-agent systems: a systematic literature review
Calegari, R., Ciatto, G., Mascardi, V., & Omicini, A. (2021) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-020-09478-3 · Cited by 117
Song, Y., & Ferretti, R. P. (2013) · Reading and Writing · doi:10.1007/s11145-012-9381-8 · Cited by 81
Metadata
- Authors
- Walton, D., Reed, C., & Macagno, F.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2008-08-04
- OpenAlex
- W581684831
- Cited by
- 1,372
- References
- 1
- FWCI
- 10.62
- Type
- book
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Argumentation Schemes. https://app.cochat.ai/papers/10.1017/cbo9780511802034
- The paper
- Walton, D., Reed, C., & Macagno, F. (2008). Argumentation Schemes. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511802034
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.