Symbolic LTLf synthesis

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Abstract

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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APA

Zhu, S., Tabajara, L. M., Li, J., Puy, G., & Vardi, M. Y. (2017). Symbolic LTLf synthesis. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 0, pp. 1362–1369). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2017/189

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