REBA : a refinement-based architecture for knowledge representation and reasoning in robotics
- Submitting institution
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The University of Birmingham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 68946231
- Type
- D - Journal article
- DOI
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10.1613/jair.1.11524
- Title of journal
- Journal of Artificial Intelligence Research
- Article number
- -
- First page
- 87
- Volume
- 65
- Issue
- -
- ISSN
- 1076-9757
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- 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
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3
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The architecture described in this article represents and reasons with incomplete commonsense domain knowledge and uncertainty using tightly-coupled transition diagrams at two different resolutions. It draws on the principle of step-wise refinement, and makes novel contributions to action languages, non-monotonic logical reasoning, and probabilistic reasoning. As a result, the architecture supports precise reasoning in the presence of uncertainty and scales to more complex domains than was possible before. This article in a high-impact journal extends well-cited conference papers, and has laid the foundation for other journal articles and externally-funded grants (~1.5M GBP as PI) over the last 3-4 years.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -