Meta-interpretive learning: application to grammatical inference
- Submitting institution
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The University of Surrey
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 9024866_3
- Type
- D - Journal article
- DOI
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10.1007/s10994-013-5358-3
- Title of journal
- Machine Learning
- Article number
- -
- First page
- 25
- Volume
- 94
- Issue
- 1
- ISSN
- 0885-6125
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
-
- Supplementary information
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-
- 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
-
-
- Research group(s)
-
-
- Citation count
- 49
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The first publication on Meta-Interpretive Learning (MIL), a powerful and novel machine learning approach. This is significant because it describes the theoretical foundation and the first implementation of MIL which have been the basis for further development and applications of MIL in several challenging problems including the learning string transformations for spreadsheet applications, learning robot strategies and learning tactics for proving correctness of programs. For example, the staircase problem in section 4.5 has led to a new framework called Logical Vision, recently applied in computer vision, e.g. for RoboCup (to appear in Machine Learning, 2018).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -