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:
- Artificial Intelligence for MDE. MDE can benefit from integrating AI concepts and ideas, for example by increasing the power and flexibility of 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.
- MDE for Artificial Intelligence. Conversely, AI can benefit from integrating concepts and ideas from MDE. For example, using domain-specific languages and model transformations 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.
Topics of interest for the workshop include, but are not limited to:
- AI for MDE:
- Application of (meta-heuristic) search to modelling problems;
- Machine learning of models, meta-models, concrete syntax, model transformations, etc.;
- AI planning applied to modelling, meta-modelling, and model management;
- Modeling bots, chatbots and virtual assistants in the modeling tasks;
- Model inferencers and automatic model generators from datasets;
- Self-adapting code generators;
- AI-based user interface adaptation for modeling tools;
- AI with human-in-the-loop for modeling;
- Semantic reasoning platforms over domain-specific models;
- Semantic integration of design-time models with runtime data;
- General-knowledge or domain-specific ontologies;
- Probabilistic models;
- Use of AI techniques in data, process and model mining and categorisation;
- Natural language processing applied to modelling;
- Perception and modelling.
- MDE for AI:
- Domain-specific modelling approaches for AI planning, machine learning, agent-based modelling, etc.;
- Model-driven processes for AI system development;
- MDE techniques for explainable AI;
- Using models for knowledge representation;
- Code-generation for AI libraries and platforms;
- Model-based testing of AI components.
- Tools for combining AI and MDE;
- Case studies in MDE Intelligence;
- Challenge problems to be addressed by combining AI and MDE techniques.
You are invited to apply for attendance by sending the following types of papers:
- Research/technical papers or work-in-progress papers of at most 6 pages,
- Vision papers, experience papers, case study papers or demos of at most 4 pages.
Submitted papers must conform to the IEEE double column format.
Submissions must be uploaded through EasyChair in the following link https://easychair.org/conferences/?conf=mdeintelligence2019.
Each submission will be review by at least 3 members of the program committee. They will value the relevance and interest for discussions that will take place at the workshop. Accepted papers will be published in the IEEE Satellite Event Proceedings.
Abstract submission: June 28, 2019 Paper submission: July 5, 2019 Notification: July 26, 2019 Camera-ready: August 2, 2019
- Workshop date: September 15-17, 2019
If you have questions, contact us by email at: firstname.lastname@example.org.