摘要翻译:
给出了从产生式系统图到MIVAR网二部图的理论转变。给出了MIVAR网在矩阵和图的形式化中的实现实例。从理论上证明了MIVAR网络的对象和规则自动生成算法的线性计算复杂度。在MIVAR网络的基础上开发了UDAV软件,在普通计算机上处理了117万多个对象和350万多条规则。实验结果证实了信息处理的MIVAR方法的线性计算复杂度。关键词:MIVAR,MIVAR网络,逻辑推理,计算复杂性,人工智能,智能系统,专家系统,通用问题求解器。
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英文标题:
《MIVAR: Transition from Productions to Bipartite Graphs MIVAR Nets and
Practical Realization of Automated Constructor of Algorithms Handling More
than Three Million Production Rules》
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作者:
Oleg O. Varlamov
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最新提交年份:
2011
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Artificial Intelligence 人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要:
The theoretical transition from the graphs of production systems to the bipartite graphs of the MIVAR nets is shown. Examples of the implementation of the MIVAR nets in the formalisms of matrixes and graphs are given. The linear computational complexity of algorithms for automated building of objects and rules of the MIVAR nets is theoretically proved. On the basis of the MIVAR nets the UDAV software complex is developed, handling more than 1.17 million objects and more than 3.5 million rules on ordinary computers. The results of experiments that confirm a linear computational complexity of the MIVAR method of information processing are given. Keywords: MIVAR, MIVAR net, logical inference, computational complexity, artificial intelligence, intelligent systems, expert systems, General Problem Solver.
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PDF链接:
https://arxiv.org/pdf/1111.1321


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