Automatic Learning for Digital Twins

Research Topic 3 (RT3) is committed to pushing the boundaries of what Digital Twins can achieve by exploring and implementing techniques based on Automatic Learning (AL)—the process of automating the tasks involved in applying Machine Learning (ML) to real-world problems. AL empowers machines with the ability to learn from data and adapt their behavior without the need for explicit programming. It is akin to giving computers the ability to interpret models, make predictions, and evolve a system’s behavior over time, mimicking the human capacity for learning and problem-solving.

AL is the cornerstone of building intelligent systems that continuously grow, refine, and innovate on their own. By seamlessly integrating real-time data and leveraging advanced AL algorithms, RT3 aims to create DTs that are not just static replicas, but dynamic, adaptive systems capable of responding to changes in real-time. This is a crucial step for DTs to establish themselves as intelligent, responsive assets that have the power to revolutionize industries through improved operational efficiency.