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arxiv: 1705.08426 · v2 · pith:F7PVVPENnew · submitted 2017-05-23 · 💻 cs.LO · cs.AI

Symbolic LTLf Synthesis

classification 💻 cs.LO cs.AI
keywords synthesissymbolicltlfapproachbooleanexplicitstrategybenchmarks
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LTLf synthesis is the process of finding a strategy that satisfies a linear temporal specification over finite traces. An existing solution to this problem relies on a reduction to a DFA game. In this paper, we propose a symbolic framework for LTLf synthesis based on this technique, by performing the computation over a representation of the DFA as a boolean formula rather than as an explicit graph. This approach enables strategy generation by utilizing the mechanism of boolean synthesis. We implement this symbolic synthesis method in a tool called Syft, and demonstrate by experiments on scalable benchmarks that the symbolic approach scales better than the explicit one.

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