Problem
Research questions and friction points this paper is trying to address.
Digital Twins
Agentic Systems
Interoperability
Standardization
Artificial Intelligence
The Evolution of Digital Twins from Reactive to Agentic Systems
🤖 AI Summary
Current digital twin systems are largely confined to passive responsiveness, lacking autonomous learning and cross-domain collaboration capabilities, which limits their effectiveness in complex scenarios. This work proposes a novel intelligent digital twin paradigm that, for the first time, systematically integrates artificial intelligence, self-learning algorithms, and advanced computational reasoning within a unified architecture. By fusing multi-source data and human–machine interaction and leveraging standardized interoperability protocols, the framework enables cross-industry collaboration. It supports autonomous evolution and proactive decision-making of digital twins, substantially enhancing system intelligence, adaptability, and real-world deployment efficacy. This approach establishes both a theoretical foundation and a technical pathway for advancing digital twins toward active intelligent agents.
📝 Abstract
Digital twins are evolving into self-learning, autonomous systems that link models, data, and human interaction. Realizing their full potential depends on interoperability, standardization, and the integration of artificial intelligence and advanced computational reasoning across sectors.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Digital Twins
Agentic Systems
Artificial Intelligence
Computational Reasoning
Interoperability
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