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Logical composition of qualitative shapes applied to solve spatial reasoning tests

机译:定性形状的逻辑组合用于解决空间推理测试

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A logical approach to compose qualitative shape descriptors (LogC-QSD) is presented in this paper. Each object shape is described qualitatively by its edges, angles, convexities, and lengths. LogC-QSD describes the shape of composed objects qualitatively adding circuits to describe the connections among the shapes. It also infers new angles and lengths using composition tables. Its main contributions are: (i) describing qualitatively the resulting boundary of connecting N shapes and (ii) its application to solve spatial reasoning tests. LogC-QSD approach has been implemented using Prolog programming language, which is based on Horn clauses and first order logic. The testing framework was SWI-Prolog on the LogC-QSD dataset. The obtained results show that the LogC-QSD approach was able to correctly answer all the questions in the LogC-QSD dataset, which involved compositions up to five shapes. The correct answer for 60% of the questions was obtained in an average time of 2.45.10(-4) s by comparing the concavities and right angles of the final QSD composed shape with the possible answers. The rest of the questions required a matching algorithm and they were solved by LogC-QSD in an average time of 19.50.10(-4) s. Analysis of the execution times obtained showed that the algorithmic cost of LogC-QSD is lower than O(n(2)) in the worst case. (C) 2018 Elsevier B.V. All rights reserved.
机译:本文提出了一种构成定性形状描述符的逻辑方法(LogC-QSD)。每个对象的形状都通过其边缘,角度,凸度和长度进行了定性描述。 LogC-QSD描述了组成对象的形状,并定性地添加了电路以描述形状之间的连接。它还可以使用成分表推断出新的角度和长度。它的主要贡献是:(i)定性描述连接的N个形状的结果边界,以及(ii)在解决空间推理测试中的应用。 LogC-QSD方法已使用Prolog编程语言实现,该语言基于Horn子句和一阶逻辑。测试框架是LogC-QSD数据集上的SWI-Prolog。获得的结果表明,LogC-QSD方法能够正确回答LogC-QSD数据集中的所有问题,涉及多达五个形状的成分。通过将最终QSD组成形状的凹度和直角与可能的答案进行比较,可以在平均时间2.45.10(-4)s中获得60%问题的正确答案。其余问题需要匹配算法,并且LogC-QSD在平均时间19.50.10(-4)s中解决了这些问题。对执行时间的分析表明,在最坏的情况下,LogC-QSD的算法成本低于O(n(2))。 (C)2018 Elsevier B.V.保留所有权利。

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