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5th Workshop on Artificial Intelligence and Model-Driven Engineering (MDE Intelligence 2023)

October 1-6, 2023. Västerås, Sweden

https://mde-intelligence.github.io/

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THEME & GOALS
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Artificial Intelligence (AI) has become part of everyone's life. It is used by companies to exploit the information they collect to improve the products and/or services they offer and, wanted or unwanted, it is present in almost every device around us. Lately, AI is also impacting all aspects of the system and software development lifecycle, from their upfront specification to their design, testing, deployment and maintenance, with the main goal of helping engineers produce systems and software faster and with better quality while being able to handle ever more complex systems and software.

There is no doubt that MDE has been a means to tame until now part of this complexity. However, its adoption by industry still relies on their capacity to manage the underlying methodological changes including among other things the adoption of new tools. To go one step further, we believe there is a clear need for AI-empowered MDE, which will push the limits of "classic" MDE and provide the right techniques to develop the next generation of highly complex model-based system and software systems engineers will have to design tomorrow.

This workshop provides a forum to discuss, study and explore the opportunities and challenges raised by the integration of AI and MDE.

We would like to address topics such as how to choose, evaluate and adapt AI techniques to Model-Driven Engineering as a way to improve current system and software modeling and generation processes in order to increase the benefits and reduce the costs of adopting MDE. We believe that AI artifacts will empower the MDE tools and boost hence the advantages, and then adoption, of MDE at industry level.

At the same time, AI is software (and complex software, in fact), we also believe that such AI-powered MDE approach will also benefit the design of AI artifacts themselves and specially to face the challenge of designing "trustable" AI software.

Last but not least, although AI is the most popular branch of computer science to create and simulate intelligence, we also believe that any kind of technique that provides human cognitive capabilities and helps creating "intelligent" software are also in the scope of this workshop. An example would be the knowledge representation techniques and ontologies that can be useful on its own or support other kinds of AI techniques.

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TOPICS OF INTEREST
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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 to increase its power: flexibility, user experience, quality, etc. 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.

* MDE for Artificial Intelligence. AI is software, and as such, it can benefit from integrating concepts and ideas from MDE that have been proven to improve software development. 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 fair and explainable AI.

Topics of interest for the workshop include, but are not limited to:

AI for MDE
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* Application of (meta-heuristic) search and machine learning to modelling problems;
* Machine learning of (meta-)models, concrete syntax, model transformations, etc.;
* AI planning applied to (meta-)modelling, and model management;
* AI-supported modelling (e.g., bots, recommenders, UI adaptation, etc.)
* Model inferencers and automatic, dataset-based model generators;
* Self-adapting code generators;
* Semantic reasoning, knowledge graphs or domain-specific ontologies;
* AI-supported model-based digital twins;
* Probabilistic, descriptive or predictive models;
* AI techniques for data, process and model mining and categorisation;
* Natural language processing applied to modelling, including Large Language Models (LLM) and Generative AI;
* Data quality and privacy issues in AI for MDE;
* Reinforcement learning to optimize modelling tasks.

MDE for AI
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* Domain-specific modelling approaches for AI planning, machine learning, agent-based modelling, etc.;
* Model-driven processes for AI system development;
* MDE techniques for explainable and fair AI;
* Using models for knowledge representation;
* Code-generation for AI libraries and platforms;
* Architectural languages for AI-enhanced systems;
* MDE for federated learning;
* Model-based testing/analysis of AI components.

General
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* AI in teaching MDE;
* Tools, frameworks, modeling standards;
* Experience reports, case studies, and empirical studies;
* Challenges.

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SUBMISSIONS
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Submissions must adhere to the IEEE formatting instructions, which can be found here. We ask for two type of contributions:

1) Research papers: 8 pages,
2) Vision papers, experience papers or demos: 5 pages.

Submissions must be uploaded through EasyChair in the following link https://easychair.org/conferences/?conf=mdeintelligence2023.

All submissions will follow a single-blind review process where each paper will be reviewed 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 joint workshop proceedings published by the IEEE.

Papers submitted to MDE Intelligence 2023 must not be under review or submitted for review elsewhere whilst under consideration for MDE intelligence 2023. Contravention of this concurrent submission policy (as stated explicity by the IEEE on https://www.comsoc.org/publications/ieee-communications-society-policy-plagiarism-and-multiple-submissions) will be deemed as a serious breach of scientific ethics, and appropriate action will be taken in all such cases.

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IMPORTANT DATES
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Paper submission: July 17, 2023
Notification: August 15, 2023
Camera-ready: August 22, 2023
Workshop: October 1-3, 2023

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PROGRAM COMMITTEE
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Shaukat Ali (Simula Research Laboratory, Norway)
Robert Clarisó (Universitat Oberta de Catalunya, Spain)
Istvan David (Université de Montréal, Canada)
Mattia Fumagalli (University of Bolzano, Italy)
Antonio Garmendia (Universidad Autónoma de Madrid, Spain)
Sébastien Gérard (CEA List, France)
Kamal Karlapalem (IIIT Hyderabad, India)
Wolfgang Maass (DFKI, Saarland University, Germany)
Phuong Nnguyen (University of L'Aquila, Italy)
Bentley Oakes (Université de Montréal, Canada)
Aurora Ramírez (University of Córdoba, Spain)
Davide di Ruscio (University of L'Aquila, Italy)
Rijul Saini (McGill University, Canada)
Daniel Strüber (Radboud University Nijmegen, Netherlands)
Gabriele Taentzer (Philipps-Universität Marburg, Germany)
Marina Tropmann-Frick (Hamburg University of Applied Sciences, Germany)
Steffen Zschaler (King’s College London, UK)

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Contact
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For additional information, clarification, or answers to questions, please contact the Organizing Committee by email at mdeintelligence2023@easychair.org