How should I compute my candidates? A taxonomy and classification of diagnosis computation algorithms
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arXiv
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| Format: | Preprint |
| Published: |
2022
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| _version_ | 1866910448593403904 |
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| author | Rodler, Patrick |
| author_facet | Rodler, Patrick |
| contents | This work proposes a taxonomy for diagnosis computation methods which allows their standardized assessment, classification and comparison. The aim is to (i) give researchers and practitioners an impression of the diverse landscape of available diagnostic techniques, (ii) allow them to easily retrieve the main features as well as pros and cons of the approaches, (iii) enable an easy and clear comparison of the techniques based on their characteristics wrt. a list of important and well-defined properties, and (iv) facilitate the selection of the "right" algorithm to adopt for a particular problem case, e.g., in practical diagnostic settings, for comparison in experimental evaluations, or for reuse, modification, extension, or improvement in the course of research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2207_12583 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | How should I compute my candidates? A taxonomy and classification of diagnosis computation algorithms Rodler, Patrick Artificial Intelligence Logic in Computer Science This work proposes a taxonomy for diagnosis computation methods which allows their standardized assessment, classification and comparison. The aim is to (i) give researchers and practitioners an impression of the diverse landscape of available diagnostic techniques, (ii) allow them to easily retrieve the main features as well as pros and cons of the approaches, (iii) enable an easy and clear comparison of the techniques based on their characteristics wrt. a list of important and well-defined properties, and (iv) facilitate the selection of the "right" algorithm to adopt for a particular problem case, e.g., in practical diagnostic settings, for comparison in experimental evaluations, or for reuse, modification, extension, or improvement in the course of research. |
| title | How should I compute my candidates? A taxonomy and classification of diagnosis computation algorithms |
| topic | Artificial Intelligence Logic in Computer Science |
| url | https://arxiv.org/abs/2207.12583 |