The DigitalTwin from an Artificial Intelligence Perspective

But two main contradictions remain: First, AI/ML are very heterogeneous, and Services for Cyber-Physical Systems based on Artificial each AI/ML method comes with a specialized model Intelligence and Machine Learning require formalism to capture relevant aspects of the environment a virtual representation of the physical. To reduce and the application domain. Hence, the modeling efforts and to synchronize results, for each question is how a DigitalTwin can provide the correct system, a common and unique virtual representation model to each AI/ML method. The second used by all services during the whole system contradiction is that AI/ML requires explicit, i.e. life-cycle is needed--i.e. a DigitalTwin. In this paper by an algorithm processable knowledge, since compiled such a DigitalTwin, namely the AI reference knowledge in form of simulation libraries, raw model AITwin, is defined. This reference model is data or executables does not help. But most publications verified by using a running example from process refer to these kind of information.