Artificial Intelligence (AI) and its subsets i.e. Deep Learning (DL), Machine Learning (ML) etc. are becoming more and more ubiquitous in engineering, technology and science. Modeling and Simulation (M&S) is no exception. I am currently engaging in a project with the objective of exploiting the synergy put forward by AI and M&S in order to propose more efficient models and results.
I understand there are various publications on this topic although I see two limitations with the publications I encountered so far: 1. The publications on AI + M&S are very application exclusive, e.g. application of DL in reservoir modeling, application of ML in fluid dynamics. 2. The application of AI in M&S usually focuses on a specific level in system hierarchy (by system hierarchy I would like to address different levels in M&S). For instance I see there are papers discussing the use of DL in analyzing the results of a simulation in order to optimize the input of the same simulation (it falls in the context of sensitivity analysis).
So bottom line is I don't see any comprehensive work on the use of AI in M&S as a whole, let's say having models that can learn how to produce new improved models using the existing models. That is to say suggesting intelligent tools capable of learning how to perform simulation solely by some input data.
Am I missing something? Did I not look careful enough to find such publications?