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We introduce the concept of structured synthesis for Markov decision processes where the structure is induced from finitely many pre-specified options for a system configuration. The resulting synthesis problem is in general a nonlinear programming problem (NLP) with integer variables. As solving NLPs is in general not feasible, we present an alternative approach. We present a transformation of models specified in the {PRISM} probabilistic programming language to models that account for all possible system configurations by means of nondeterministic choices. Together with a control module that ensures consistent configurations throughout the system, this transformation enables the use of optimized tools for model checking in a black-box fashion. While this transformation increases the size of a model, experiments with standard benchmarks show that the method provides a feasible approach for structured synthesis. Moreover, we demonstrate the usefulness along a realistic case study involving surveillance by unmanned aerial vehicles in a shipping facility.
Probabilistic programs are key to deal with uncertainty in e.g. controller synthesis. They are typically small but intricate. Their development is complex and error prone requiring quantitative reasoning over a myriad of alternative designs. To mitig
Many systems are naturally modeled as Markov Decision Processes (MDPs), combining probabilities and strategic actions. Given a model of a system as an MDP and some logical specification of system behavior, the goal of synthesis is to find a policy th
We consider MAP estimators for structured prediction with exponential family models. In particular, we concentrate on the case that efficient algorithms for uniform sampling from the output space exist. We show that under this assumption (i) exact co
The assurance of quality of service properties is an important aspect of service-oriented software engineering. Notations for so-called service level agreements (SLAs), such as the Web Service Level Agreement (WSLA) language, provide a formal syntax
Providing compact and understandable counterexamples for violated system properties is an essential task in model checking. Existing works on counterexamples for probabilistic systems so far computed either a large set of system runs or a subset of t