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Finding similar/diverse solutions in answer set programming

机译:在答案集编程中找到相似/多样化的解决方案

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摘要

For some computational problems (e.g., product configuration, planning, diagnosis, query answering, phylogeny reconstruction), computing a set of similar/diverse solutions may be desirable for better decision-making. With this motivation, we have studied several decision/optimization versions of this problem in the context of Answer set programming (ASP), analyzed their computational complexity, and introduced offline/online methods to compute similar/diverse solutions of such computational problems with respect to a given distance function. All these methods rely on the idea of computing solutions to a problem by means of finding the answer sets for an ASP program that describes the problem. The offline methods compute all solutions of a problem in advance using the ASP formulation of the problem with an existing ASP solver, like clasp, and then identify similar/diverse solutions using some clustering methods (possibly in ASP as well). The online methods compute similar/diverse solutions of a problem following one of the three approaches: by reformulating the ASP representation of the problem to compute similar/diverse solutions at once using an existing ASP solver; by computing similar/diverse solutions iteratively (one after the other) using an existing ASP solver; by modifying the search algorithm of an ASP solver to compute similar/diverse solutions incrementally. All these methods are sound; the offline method and the first online method are complete whereas the others are not. We have modified clasp to implement the last online method and called it clasp-nk. In the first two online methods, the given distance function is represented in ASP; in the last one, however, it is implemented in C++. We have shown the applicability and the effectiveness of these methods using clasp or clasp-nk on two sorts of problems with different distance measures: on a real-world problem in phylogenetics (i.e., reconstruction of similar/diverse phylogenies for Indo-European languages), and on several planning problems in a well-known domain (i.e., Blocks World). We have observed that in terms of computational efficiency (both time and space), the last online method outperforms the others; also, it allows us to compute similar/diverse solutions when the distance function cannot be represented in ASP (e.g., due to some mathematical functions not supported by the ASP solvers) but can be easily implemented in C++.
机译:对于某些计算问题(例如,产品配置,计划,诊断,查询回答,系统发育重建),可能需要计算一组相似/多样化的解决方案才能做出更好的决策。出于这种动机,我们在答案集编程(ASP)的背景下研究了该问题的几种决策/优化版本,分析了它们的计算复杂性,并介绍了离线/在线方法来计算此类计算问题的相似/不同解。给定的距离函数。所有这些方法都通过找到描述问题的ASP程序的答案集来依靠计算问题解决方案的思想。脱机方法使用现有的ASP求解器(例如,带扣)使用问题的ASP公式预先计算问题的所有解决方案,然后使用某些聚类方法(可能也在ASP中)识别相似/不同的解决方案。在线方法遵循以下三种方法之一来计算问题的相似/多样化解决方案:通过重新构造问题的ASP表示,以使用现有的ASP求解器立即计算相似/多样化解决方案;通过使用现有的ASP求解器迭代(一个接一个)地计算相似/多样化的解决方案;通过修改ASP求解器的搜索算法,以递增方式计算相似/多样化的解决方案。所有这些方法都是合理的。离线方法和第一个在线方法是完整的,而其他方法则不是。我们修改了clasp来实现最后一个在线方法,并将其称为clasp-nk。在前两种在线方法中,给定的距离函数用ASP表示;但是,在最后一篇中,它是用C ++实现的。我们已经显示了使用clasp或clasp-nk的方法在两种具有不同距离度量的问题上的适用性和有效性:在系统发育学中的实际问题上(即,印欧语系相似/不同系统发育的重建) ,以及知名领域(例如,Blocks World)中的几个规划问题。我们已经观察到,就计算效率(时间和空间)而言,最后一种在线方法要优于其他方法。同样,当距离函数无法用ASP表示时(例如,由于一些ASP求解器不支持的数学函数),但可以在C ++中轻松实现,它使我们能够计算相似/不同的解。

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