In this paper, a possibilistic disjunctive logic programming approach for
modeling uncertain, incomplete and inconsistent information is defined. This
approach introduces the use of possibilistic disjunctive clauses which are able
to capture incomplete information and incomplete states of a knowledge base at
the same time.
By considering a possibilistic logic program as a possibilistic logic theory,
a construction of a possibilistic logic programming semantic based on answer
sets and the proof theory of possibilistic logic is defined. It shows that this
possibilistic semantics for disjunctive logic programs can be characterized by
a fixed-point operator. It is also shown that the suggested possibilistic
semantics can be computed by a resolution algorithm and the consideration of
optimal refutations from a possibilistic logic theory.
In order to manage inconsistent possibilistic logic programs, a preference
criterion between inconsistent possibilistic models is defined; in addition,
the approach of cuts for restoring consistency of an inconsistent possibilistic
knowledge base is adopted. The approach is illustrated in a medical scenario.

定义了一种适用于建模不确定、不完整和不一致信息的可能性析取逻辑编程方法，并介绍了可能性析取子句的使用，该子句能够同时捕捉知识库的不完全信息和不完全状态；同时基于经典答案集语义和可能性逻辑证明理论构建可能性逻辑编程语义，对于不一致可能性逻辑程序的管理，采用偏好标准和切割方法进行篡改，并以医学场景为例进行了说明。