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- W1489533938 abstract "AbstractThe extended answer set semantics for simple logic programs, i.e. programs with only classical negation, allows for the defeat of rules to resolve contradictions. In addition, a partial order relation on the program’s rules can be used to deduce a preference relation on its extended answer sets. In this paper, we propose a “quantitative” preference relation that associates a weight with each rule in a program. Intuitively, these weights define the “cost” of defeating a rule. An extended answer set is preferred if it minimizes the sum of the weights of its defeated rules. We characterize the expressiveness of the resulting semantics and show that it can capture negation as failure. Moreover the semantics can be conveniently extended to sequences of weight preferences, without increasing the expressiveness. We illustrate an application of the approach by showing how it can elegantly express subgraph isomorphic approximation problems, a concept often used in intelligence analysis to find specific regions of interest in a large graph of observed activities.KeywordsLogic ProgramLogic ProgrammingActivity GraphIntelligence AnalysisStable Model SemanticThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W1489533938 date "2005-01-01" @default.
- W1489533938 modified "2023-09-25" @default.
- W1489533938 title "Weighted Answer Sets and Applications in Intelligence Analysis" @default.
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- W1489533938 doi "https://doi.org/10.1007/978-3-540-32275-7_12" @default.
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