Using SAT/SMT Solvers for Efficiently Tuning Fuzzy Logic Programs
Using SAT/SMT Solvers for Efficiently Tuning Fuzzy Logic Programs
复制标题
使用 SAT/SMT 求解器有效调整模糊逻辑程序
DOI：
10.1109/fuzz48607.2020.9177798
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Ginés Moreno
中科院分区：
文献类型：
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作者：
J. A. Riaza;Ginés Moreno
在过去的几年中，我们已经开发出先进的工具，用于调整模糊逻辑程序，致力于促进选择更合适的一套权重和模糊连接程序中使用的规则。设计精确的技术来自动化这些任务对程序员来说是非常有用的，即使它们很耗时。为了提高其性能，在本文中，我们利用强大的和著名的SAT/SMT求解器，以改善我们原来的方法。我们已经获得了一些以前的经验，在这种情况下，其影响越来越大，在许多现代软件工具的启发，我们展示了一些代表性的实验（相关的电路验证和线性回归）和基准，说明了新的授权方法所享有的显着优势。
During the last years we have developed advanced tools for tuning fuzzy logic programs devoted to facilitate the selection of the more appropriate set of weights and fuzzy connectives used in programs rules. Designing accurate techniques for automating these tasks is very useful for programmers, even when they are time consuming. In order to increase its performance, in this paper we make use of powerful and well-known SAT/SMT solvers for improving our original approaches. Inspired by some previous experiences we have acquired in this setting, whose impact is growing in many modern software tools, we show some representative experiments (related to circuit validation and linear regression) and benchmarks which illustrate the significant advantages enjoyed by the new empowered method.