部分演绎在谓词演算中作为人工智能问题复杂性降低的工具

2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2015-12-01 DOI:10.1109/INTELCIS.2015.7397199

T. Kosovskaya

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引用次数: 1

摘要

许多人工智能问题都是np完全问题。为了减少求解此类问题所需的时间，提出了一种提取表征所考虑对象的共同特征的子公式的方法。该方法基于作者提出的部分演绎概念。重复应用这个过程可以形成一个对象和对象类的层次描述。文中给出了这种层次描述和阶数递增程度的一个模型实例。

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Partial deduction in predicate calculus as a tool for artificial intelligence problem complexity decreasing

Many artificial intelligence problems are NP-complete ones. To decrease the needed time of such a problem solving a method of extraction of sub-formulas characterizing the common features of objects under consideration is suggested. This method is based on the offered by the author notion of partial deduction. Repeated application of this procedure allows to form a level description of an object and of classes of objects. A model example of such a level description and the degree of steps number increasing is presented in the paper.

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2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)

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