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arXiv 1109.6401cs.LOcs.AImath.LO
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信念函数的概率多模态逻辑解释

An Interpretation of Belief Functions by means of a Probabilistic Multi-modal Logic

ENSTA Bretagne(布列塔尼国立高等先进技术学院)

Frederic Dambreville

摘要:

虽然信度函数可以被正式地看作是概率分布的推广,但信度函数和概率之间的相互作用问题在实践中仍然是一个问题。这个问题是困难的,因为这些理论的使用背景明显不同,这些理论背后的语义并不完全相同。一个日益受到社会关注的突出问题,就是对冲突信息的管理。最近的作品介绍了新的规则,处理冲突的重新分配,同时结合信念功能。冲突的概念,或其取消开放世界的假设,似乎本身就阻止了直接解释的信念函数的概率框架。本文讨论的问题的概率解释的信念功能。它首先介绍并实现了一个理论上的接地规则,这在本质上是一个自适应合取规则。它示出,如何从逻辑解释的置信函数的概率多模态逻辑,这一规则是来自;此外,引入了一个概念的源独立性,基于熵最大化的原则。

英文摘要:

While belief functions may be seen formally as a generalization of probabilistic distributions, the question of the interactions between belief functions and probability is still an issue in practice. This question is difficult, since the contexts of use of these theory are notably different and the semantics behind these theories are not exactly the same. A prominent issue is increasingly regarded by the community, that is the management of the conflicting information. Recent works have introduced new rules for handling the conflict redistribution while combining belief functions. The notion of conflict, or its cancellation by an hypothesis of open world, seems by itself to prevent a direct interpretation of belief function in a probabilistic framework. This paper addresses the question of a probabilistic interpretation of belief functions. It first introduces and implements a theoretically grounded rule, which is in essence an adaptive conjunctive rule. It is shown, how this rule is derived from a logical interpretation of the belief functions by means of a probabilistic multimodal logic; in addition, a concept of source independence is introduced, based on a principle of entropy maximization.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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