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Knowledge-intensive Processes (KiPs) are processes characterized by high levels of unpredictability and dynamism. Their process structure may not be known before their execution. One way to cope with this uncertainty is to defer decisions regarding the process structure until run time. In this paper, we consider the definition of the process structure as a planning problem. Our approach uses automated planning techniques to generate plans that define process models according to the current context. The generated plan model relies on a metamodel called METAKIP that represents the basic elements of KiPs. Our solution explores Markov Decision Processes (MDP) to generate plan models. This technique allows uncertainty representation by defining state transition probabilities, which gives us more flexibility than traditional approaches. We construct an MDP model and solve it with the help of the PRISM model-checker. The solution is evaluated by means of a proof of concept in the medical domain which reveals the feasibility of our approach.

Socio-technical systems are characterized by the interplay of heterogeneous entities i.e., humans, organizations, and technologies. Application domains such as petroleum, e-health, and many others rely on solutions based on safety-critical socio-technical systems. To ensure a safe operation of these interacting heterogeneous entities, multifaceted and integrated modeling and analysis capabilities are needed. Currently, such capabilities are not at disposal. To contribute to the provision of such capabilities, in this paper we propose SafeConcert, a metamodel that offers constructs to model socio-technical entities and their safety-related properties. SafeConcert also represents a unified and harmonized language that supports the integrated application of qualitative as well as quantitative safety analyses techniques. To support our claims we briefly report about the evaluation that was conducted and documented in the context of the EU CONCERTO project.