Towards Engineering Cognitive Digital Twins with Self-Awareness
Nan Zhang, Rami Bahsoon, Georgios Theodoropoulos
Abstract
There has been a recent explosion of interest in digital twins, namely data driven virtual replicas that can provide insights about a physical system and support decision making. This paper deals with cognitive digital twins, namely twins that can exhibit a high level of intelligence that can replicate human cognitive processes and execute conscious actions autonomously. The paper brings together the concepts of digital twins and self-awareness and discusses how the different levels of self-awareness can be harnessed for the design of cognitive-digital twins. A discussion of digital twins in relation to the Dynamic Data Driven Application Systems (DDDAS) paradigm and a classification of digital twins based on their analytics capability are also provided.