Argument Calculus and Networks
UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence(2013)
摘要
A major reason behind the success of probability calculus is that it possesses a number of valuable tools, which are based on the notion of probabilistic independence. In this paper, I identify a notion of logical independence that makes some of these tools available to a class of propositional databases, called argument databases. Specifically, I suggest a graphical representation of argument databases, called argument networks, which resemble Bayesian networks. I also suggest an algorithm for reasoning with argument networks, which resembles a basic algorithm for reasoning with Bayesian networks. Finally I show that argument networks have several applications: Nonmonotonic reasoning, truth maintenance, and diagnosis.
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关键词
basic algorithm,graphical representation,logical independence,bayesian network,argument network,argument calculus,major reason,nonmonotonic reasoning,probabilistic independence,propositional databases,argument databases
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