Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. In this paper, we consider the computational aspects of inconsistency degrees of propositional knowledge bases under 4-valued semantics. We first give a complete analysis of the computational complexity of computing inconsistency degrees. As it turns out that computing the exact inconsistency degree is intractable, we then propose an anytime algorithm that provides tractable approximations of the inconsistency degree from above and below. We show that our algorithm satisfies some desirable properties and give experimental results of our implementation of the algorithm

VL - 4 UR - http://www.ijsi.org/ch/reader/view_abstract.aspx?file_no=i41&flag=1 ER - TY - CONF T1 - An Anytime Algorithm for Computing Inconsistency Measurement T2 - Knowledge Science, Engineering and Management, Third International Conference, KSEM 2009 Y1 - 2009 A1 - Yue Ma A1 - Guilin Qi A1 - Guohui Xiao A1 - Pascal Hitzler A1 - Zuoquan Lin ED - Dimitris Karagiannis ED - Zhi Jin AB -Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. In this paper, we consider the computational aspects of inconsistency degrees of propositional knowledge bases under 4-valued semantics. We first analyze its computational complexity. As it turns out that computing the exact inconsistency degree is intractable, we then propose an anytime algorithm that provides tractable approximation of the inconsistency degree from above and below. We show that our algorithm satisfies some desirable properties and give experimental results of our implementation of the algorithm.

JF - Knowledge Science, Engineering and Management, Third International Conference, KSEM 2009 PB - Springer CY - Vienna, Austria VL - 5914 UR - http://dx.doi.org/10.1007/978-3-642-10488-6_7 ER -