  In the era of Big Data and Internet-of-Things (IoT), all real-world
environments are gradually becoming cyber-physical (e.g., emergency management,
healthcare, smart manufacturing, etc.), with the presence of connected devices
and embedded ICT systems (e.g., smartphones, sensors, actuators) producing huge
amounts of data and events that influence the enactment of the Cyber Physical
Processes (CPPs) enacted in such environments. A Process Management System
(PMS) employed for executing CPPs is required to automatically adapt its
running processes to anomalous situations and exogenous events by minimising
any human intervention at run-time. In this paper, we tackle this issue by
introducing an approach and an adaptive Cognitive PMS that combines process
execution monitoring, unanticipated exception detection and automated
resolution strategies leveraging on well-established action-based formalisms in
Artificial Intelligence, which allow to interpret the ever-changing knowledge
of cyber-physical environments and to adapt CPPs by preserving their base
structure.
