Abstract
While a boolean notion of correctness is given by a preorder on systems and properties, a quantitative notion of correctness is defined by a distance function on systems and properties, where the distance between a system and a property provides a measure of “fit” or “desirability.” In this article, we explore several ways how the simulation preorder can be generalized to a distance function. This is done by equipping the classical simulation game between a system and a property with quantitative objectives. In particular, for systems that satisfy a property, a quantitative simulation game can measure the “robustness” of the satisfaction, that is, how much the system can deviate from its nominal behavior while still satisfying the property. For systems that violate a property, a quantitative simulation game can measure the “seriousness” of the violation, that is, how much the property has to be modified so that it is satisfied by the system. These distances can be computed in polynomial time, since the computation reduces to the value problem in limit average games with constant weights. Finally, we demonstrate how the robustness distance can be used to measure how many transmission errors are tolerated by error correcting codes.
This work was partially supported by the European Union project COMBEST and the European Network of Excellence ArtistDesign.
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Černý, P., Henzinger, T.A., Radhakrishna, A. (2010). Quantitative Simulation Games . In: Manna, Z., Peled, D.A. (eds) Time for Verification. Lecture Notes in Computer Science, vol 6200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13754-9_3
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