Abstract
Model-driven engineering (MDE) and artificial intelligence (AI) are two separate fields in computer science, which can clearly benefit from cross-pollination and collaboration. There are at least two ways in which such integration—which we call MDE Intelligence—can manifest: (1) MDE can benefit from integrating AI concepts and ideas to increase its power: flexibility, user experience, quality, etc. (Artificial Intelligence for MDE). For example, using model transformations through search-based approaches, or by increasing the ability to abstract from partially formed, manual sketches into fully-shaped and formally specified meta-models and editors. (2) AI is software, and as such, it can benefit from integrating concepts and ideas from MDE that have been proven to improve software development (MDE for Artificial Intelligence). For example, using domain-specific languages allows domain experts to directly express and manipulate their problems while providing an auditable conversion pipeline. Together this can improve trust in and safety of AI technologies. Similarly, MDE technologies can contribute to the goal of explainable AI.
| Original language | English |
|---|---|
| Title of host publication | 2nd Workshop on Artificial Intelligence and Model-driven Engineering. co-located with MODELS, 16 October 2020. |
| Number of pages | 10 |
| Publication status | Published - Oct 2020 |
Fields of science
- 202017 Embedded systems
- 102002 Augmented reality
- 102006 Computer supported cooperative work (CSCW)
- 102015 Information systems
- 102020 Medical informatics
- 102022 Software development
- 102034 Cyber-physical systems
- 201132 Computational engineering
- 201305 Traffic engineering
- 207409 Navigation systems
- 502032 Quality management
- 502050 Business informatics
- 503015 Subject didactics of technical sciences
JKU Focus areas
- Digital Transformation
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