A scale-free model for random ASP programs
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Su, Kaile
Wang, Zhe
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Liu, J
Lu, J
Xu, Y
Martinez, L
Kerre, EE
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Belfast, IRELAND
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Abstract
Scale-free property, which means a small number of nodes dominate a network with far more number of connections than other nodes, has been observed in many large-scale real-world networks and many large software systems. However, this is not investigated for answer set programming (ASP), a major paradigm of declarative problem solving. This paper first presents a generator (model) for randomly generating ASP programs that demonstrate scale-free property. Then reports that all the 28 real ASP programs from different domain showing clear scale-free property. Finally significant experiments are conducted to demonstrate that random generated ASP programs could be solved in polynomial time if they are scale-free, while general random ASP programs are NP hard problems. The results may help to understand the nature of large ASP programs.
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DATA SCIENCE AND KNOWLEDGE ENGINEERING FOR SENSING DECISION SUPPORT
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11
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Artificial intelligence not elsewhere classified