Nested Nets for Adaptive Systems

We consider nested nets, i.e. Petri nets in which tokens can be Petri nets themselves. We study the value semantics of nested nets rather than the reference semantics, and apply nested nets to model adaptive workflow, i.e. flexible workflow that can be modified during the execution. A typical domain with a great need for this kind of workflow is health care, from which domain we choose the running example. To achieve the desired flexibility we allow transitions that create new nets out of the existing ones. Therefore, nets with completely new structure can be created at the run time. We show that by careful selection of basic operations on the nets we can obtain a powerful modeling formalism that enforces correctness of models. Moreover, the formalism can be implemented based on existing workflow engines.