The logical and probabilistic bases of the calculus of evidence

E. Ruspini
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Abstract

Summary form only given. The approach proposed by R. Carnap (1962) to the development of logical bases for probability theory is applied to structures based on epistemic logic. The resulting structure, called the epistemic universe, consists of joint descriptions of possible states of the world as well as of the states of knowledge rational agents have regarding it. Special algebras of subsets of the epistemic universe are then defined. Probabilities defined over one of these classes, called the epistemic algebra (representing similar states of knowledge), are directly related to the basic functional structures of the Dempster-Shafer calculus of evidence: belief and mass assignment functions. Extensions of these probability functions to the truth algebra (representing true states of real world), must satisfy the well-known bounds of the Dempster-Shafer theory. Furthermore, these bounds are the best possible. Consideration of multiple agents leads both to more complex epistemic structures and to the derivation of a basic formula for the combination of knowledge, called the additive combination formula. From this formula and certain independence assumptions, Dempster's rule of combination is readily derived.<>
证据计算的逻辑和概率基础
只提供摘要形式。R. Carnap(1962)提出的发展概率论逻辑基础的方法适用于基于认知逻辑的结构。由此产生的结构被称为认知宇宙,它由对世界可能状态的联合描述以及理性主体对世界的知识状态的联合描述组成。然后定义了认知域子集的特殊代数。在这些类中定义的概率,称为认知代数(表示相似的知识状态),与Dempster-Shafer证据演算的基本功能结构:信念和质量分配函数直接相关。将这些概率函数扩展到真代数(表示真实世界的真状态),必须满足众所周知的Dempster-Shafer理论的边界。此外,这些界限是最好的可能。考虑多个智能体会导致更复杂的认知结构和知识组合的基本公式的推导,称为加性组合公式。从这个公式和一定的独立性假设,可以很容易地推导出Dempster的组合规则。
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