-------- Forwarded Message -------- Subject: [WI] CfP: 2nd Workshop on Artificial Intelligence and Model-driven Engineering (MDE Intelligence 2020) @ Models 2020 Date: Wed, 10 Jun 2020 09:29:04 +0200 From: Manuel Wimmer manuel.wimmer@jku.at Reply-To: Manuel Wimmer manuel.wimmer@jku.at To: wi@lists.kit.edu
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2nd Workshop on Artificial Intelligence and Model-driven Engineering (MDE Intelligence 2020)
18-20 October 2020
Montreal, Canada
https://mde-intelligence.github.io/
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-=-=-=-=-=-=-=- Theme & Goals -=-=-=-=-=-=-=-
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 starting to impact 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. The hope is that AI will help dealing with the increasing complexity of 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 industrial 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 an 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.
-=-=-=-=-=-=-=-=-=- TOPICS OF INTEREST -=-=-=-=-=-=-=-=-=-
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 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 assistants such as bots, chatbots and virtual assistants/recommenders supporting diverse 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 modeling.
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.
General =-=-=-=- * Tools for combining AI and MDE; * Case studies in MDE Intelligence; * Challenge problems to be addressed by combining AI and MDE techniques.
=-=-=-=-=-=- SUBMISSIONS =-=-=-=-=-=-
Papers will follow the same style and format of the main tracks of the conference (please check them here). We ask for two type of contributions:
1) Work-in-progress papers: 10 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=mdeintelligence2020.
Each submission 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 ACM Satellite Event Proceedings.
=-=-=-=-=-=-=-=-= IMPORTANT DATES =-=-=-=-=-=-=-=-=
Abstract submission: July 15, 2020 Paper submission: July 22, 2020 Notification: August 21, 2020 Camera-ready: August 28, 2020
=-=-=-=-=-=-=-=-=-= PROGRAM COMMITTEE =-=-=-=-=-=-=-=-=-=
Gregor Engels (University of Paderborn) Moharram Challenger (University of Antwerp) Shekoufeh Kolahdouz Rahimi (University of Isfahan) Aurora Ramírez (University of Córdoba) Gunter Mussbacher (McGill University) Shaukat Ali (Simula Research Laboratory) Nelly Bencomo (Aston University) Francisco Chicano (University of Málaga) Daniel Strüber (Chalmers University & University of Gothenburg) Adrian Rutle (Western Norway University of Applied Sciences) Daniel Varro (McGill University & Budapest University of Technology and Economics) Talbi El-Ghazali (University of Lille) Gabriele Taentzer (Philipps-Universität Marburg) Bernhard Rumpe (RWTH Aachen University) Betty Cheng (Michigan State University) Shuai Li (CEA LIST) Sandeep Neema (Vanderbilt University)
-=-=-=-=-=- Contact -=-=-=-=-=-
For additional information, clarification, or answers to questions, please contact the Organizing Committee (Loli Burgueño, Steffen Zschaler and Manuel Wimmer) by email at mdeintelligence2020@easychair.org mailto:mdeintelligence2020@easychair.org