Post by Quentin Brilhault

🚀 I am pleased to share our latest publication in the Journal of Industrial Information Integration (available via https://lnkd.in/et7ZsS9W) : "Reinforcement Learning for Model Transformations to Support Model-Driven Plug-and-Play Interoperability" As industries increasingly rely on the Digital Thread to connect data, models, systems, and stakeholders across the product lifecycle, achieving seamless interoperability remains a major challenge. The continuous evolution of technologies, standards, and business ecosystems requires interoperability mechanisms that are not only effective but also adaptive and resilient. In this work, we present a novel approach based on reinforcement learning to automatically generate model-to-model transformations, a key enabler of structural and semantic interoperability within Model-Driven Engineering frameworks. 🔹 Automated generation of transformation rules between heterogeneous models 🔹 Reduced engineering effort and faster interoperability deployment 🔹 Support for self-configuring and self-adjusting plug-and-play architectures 🔹 Contribution to resilient and scalable Digital Thread implementations Many thanks to my co-authors, Esma YAHIA and Roucoules Lionel, for this exciting collaboration. #Industry40 #DigitalThread #Interoperability #ModelDrivenEngineering #ReinforcementLearning #ArtificialIntelligence #SystemsEngineering