Finding most probable worlds of probabilistic logic programs

被引:0
|
作者
Khuller, Samir [1 ]
Martinez, Vanina [1 ]
Nan, Dana [1 ]
Simari, Gerardo [1 ]
Sliva, Amy [1 ]
Subrahmanian, V. S. [1 ]
机构
[1] Univ Maryland, College Pk, MD 20742 USA
基金
美国国家科学基金会;
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Probabilistic logic programs have primarily studied the problem of entailment of probabilistic atoms. However, there are some interesting applications where we are interested in finding a possible world that is most probable. Our first result shows that the problem of computing such "maximally probable worlds" (MPW) is intractable. We subsequently show that we can often greatly reduce the size of the linear program used in past work (by Ng and Subrahmanian) and yet solve the problem exactly. However, the intractability results still make computational efficiency quite impossible. We therefore also develop several heuristics to solve the MPW problem and report extensive experimental results on the accuracy and efficiency of such heuristics.
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页码:45 / +
页数:2
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