Our research on the Inference of Simulation Models in Digital Twins by Reinforcement Learning has been awarded the IVADO Postdoctoral Research Funding for two years.
IVADO (Institut de valorisation des données) is a Québec-wide collaborative institute in the field of digital intelligence, dedicated to transforming new scientific discoveries into concrete applications and benefits for all of society. The prestigious Postdoctoral Research Funding aims to foster development of collaborative and applied cutting-edge research, especially in the areas of operations research, machine learning and decision science.
Our research focuses on the development of simulators employed in Digital Twins. Due to the significant complexity of systems subject to digital twinning, constructing simulators of appropriate details is a costly and error-prone endeavor. To alleviate these problems, we propose an approach for inferring simulation models of Digital Twins by machine learning. Instead of learning the simulation model of one specific simulator, we aim at learning their construction process. This generality enables reusing the inferred knowledge in different (but congruent) Digital Twin settings. To achieve this level of generality, we propose the Discrete Event System Specification (DEVS) formalism for capturing simulation models; and reinforcement learning (RL) for inferring DEVS models.
More details are available in our latest vision paper accepted for this year’s International Workshop on Model-Driven Engineering of Digital Twins, co-located with MODELS. Join my talk on the topic on the 12th of October at 17:15 CET!