From fine-grained properties to broad principles for gradual argumentation: A principled spectrum
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2408
- Type
- D - Journal article
- DOI
-
10.1016/j.ijar.2018.11.019
- Title of journal
- International Journal of Approximate Reasoning
- Article number
- -
- First page
- 252
- Volume
- 105
- Issue
- 1
- ISSN
- 0888-613X
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
10.1016/j.ijar.2018.11.019
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper presents novel principles for a class of 'gradual' semantics for computational argumentation, which is a form of reasoning extensively studied in AI over the past two decades. It provides a definitive, original synthesis of work in this space, including a large number of existing properties and methods for gradual argumentation. It extends two papers from AAAI'18 (https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewPaper/16280; acceptance rate: 24.6%) and SUM'18 (https://link.springer.com/chapter/10.1007/978-3-030-00461-3_17). The properties presented in the paper have driven the mining of argumentation frameworks for explanation of recommender systems, e.g. see IJCAI'18 paper (https://www.ijcai.org/proceedings/2018/269) and AAMAS'19 paper (https://dl.acm.org/citation.cfm?id=3331830).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
