Multiple Contraction Through Partial-Max-SAT

被引:1
作者
Gregoire, Eric [1 ]
Lagniez, Jean-Marie
Mazure, Bertrand
机构
[1] Univ Artois, F-62307 Lens, France
来源
2014 IEEE 26TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI) | 2014年
关键词
Partial-Max-SAT; Multiple Contraction; Knowledge Representation; Belief Change;
D O I
10.1109/ICTAI.2014.56
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An original encoding of multiple contraction in Boolean logic through Partial-Max-SAT is proposed. Multiple contraction of a set of clauses Delta by a set of formulas Gamma delivers one maximum cardinality subset of Delta from which no formula of G can be deduced. Equivalently, multiple contraction can be defined as the extraction of one maximum cardinality subset of Delta that is satisfiable together with a given set of formulas. Noticeably, the encoding schema allows multiple contraction to be computed through a number of calls to a SAT solver that is bound by the number of formulas in Gamma and one call to Partial-Max-SAT. On the contrary, in the worst case, a direct approach requires us to compute for each formula gamma in Gamma all inclusion-maximal subsets of Delta that do not entail gamma. Extensive experimental results show that the encoding allows multiple contraction to be computed in a way that is practically viable in many cases and outperforms the direct approach.
引用
收藏
页码:321 / 327
页数:7
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