Accelerating SAT Based Planning with Incremental SAT Solving

被引：0

作者：

Gocht, Stephan ^{[1
]}

Balyo, Tomas ^{[1
]}

机构：

[1] Karlsruhe Inst Technol, Karlsruhe, Germany

来源：

TWENTY-SEVENTH INTERNATIONAL CONFERENCE ON AUTOMATED PLANNING AND SCHEDULING | 2017年

关键词：

SATISFIABILITY;

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：

One of the most successful approaches to automated planning is the translation to propositional satisfiability (SAT). We employ incremental SAT solving to increase the capabilities of several modern encodings for SAT based planning. Experiments based on benchmarks from the 2014 International Planning Competition show that an incremental approach significantly outperforms non incremental solving. Although we are using sequential scheduling of makespans, we can outperform the state-of-the-art SAT based planning system Madagascar in the number of solved instances.

引用

页码：135 / 139

页数：5

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