DSmT简介

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摘要翻译：
不确定的、不精确的、模糊的、甚至矛盾的或高度冲突的信息源的管理和组合，对于发展涉及人工推理的可靠的现代信息系统来说，一直是而且今天仍然是至关重要的。在这篇引言中，我们介绍了我们最近的似是而非的推理理论，称为Dezert-Smarandache理论(DSmT)，它是为处理不精确的、不确定的和相互冲突的信息源而发展起来的。我们把重点放在DSmT的基础和它最重要的组合规则上，而不是在文献中浏览DSmT的具体应用。本文给出了几个简单的例子来说明这种新方法的有效性和通用性。
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英文标题：
《An introduction to DSmT》
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作者：
Jean Dezert (ONERA), Florentin Smarandache
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最新提交年份：
2009
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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 management and combination of uncertain, imprecise, fuzzy and even paradoxical or high conflicting sources of information has always been, and still remains today, of primal importance for the development of reliable modern information systems involving artificial reasoning. In this introduction, we present a survey of our recent theory of plausible and paradoxical reasoning, known as Dezert-Smarandache Theory (DSmT), developed for dealing with imprecise, uncertain and conflicting sources of information. We focus our presentation on the foundations of DSmT and on its most important rules of combination, rather than on browsing specific applications of DSmT available in literature. Several simple examples are given throughout this presentation to show the efficiency and the generality of this new approach.
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PDF链接：
https://arxiv.org/pdf/0903.0279

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