## Weighted Branching Simulation Distance for Parametric Weighted Kripke Structures

 Louise Foshammer (Aalborg University) Kim Guldstrand Larsen (Aalborg University) Anders Mariegaard (Aalborg University)

 This paper concerns branching simulation for weighted Kripke structures with parametric weights. Concretely, we consider a weighted extension of branching simulation where a single transitions can be matched by a sequence of transitions while preserving the branching behavior. We relax this notion to allow for a small degree of deviation in the matching of weights, inducing a directed distance on states. The distance between two states can be used directly to relate properties of the states within a sub-fragment of weighted CTL. The problem of relating systems thus changes to minimizing the distance which, in the general parametric case, corresponds to finding suitable parameter valuations such that one system can approximately simulate another. Although the distance considers a potentially infinite set of transition sequences we demonstrate that there exists an upper bound on the length of relevant sequences, thereby establishing the computability of the distance.

In Thomas Brihaye, Benoît Delahaye, Loïg Jezequel, Nicolas Markey and Jiří Srba: Proceedings Cassting Workshop on Games for the Synthesis of Complex Systems and 3rd International Workshop on Synthesis of Complex Parameters (Cassting'16/SynCoP'16), Eindhoven, The Netherlands, April 2-3, 2016, Electronic Proceedings in Theoretical Computer Science 220, pp. 63–75.
Published: 31st July 2016.

 ArXived at: http://dx.doi.org/10.4204/EPTCS.220.6 bibtex PDF
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