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A Static Model-Based Engine for Model-Based Reasoning

机译:用于模型推理的基于模型的静态引擎

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Most systems for mode-based reasoning record justifications during the search for solutions. In the popular ATMS systems this can lead to an explosion of recorded information when solving complicated problems. We propose an engine for model-based reasoning which works directly on logical models, uses static precompiled information on the structure of the underlying theory and does no further recording during search. This engine (DRUM-II) solves large complicated problems with attractive time and space complexity. To demonstrate the efficinecy of the engine we give a new characterization of a popularbenchmark suite, solve it with our engine and compare the performance to previous results.
机译:大多数基于模式的推理系统在搜索解决方案时会记录理由。在流行的ATMS系统中,当解决复杂的问题时,这可能导致记录的信息激增。我们提出了一种用于基于模型的推理的引擎,该引擎可直接在逻辑模型上工作,在基础理论的结构上使用静态的预编译信息,并且在搜索过程中无需进一步记录。该引擎(DRUM-II)以引人注目的时间和空间复杂性解决了大型复杂问题。为了演示引擎的功效,我们对流行的基准套件进行了新的描述,使用我们的引擎对其进行了求解,并将性能与以前的结果进行了比较。

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