A Software System for the Computation, Visualization, and Comparison of Conditional Structures for Relational Probabilistic Knowledge Bases
نویسندگان
چکیده
Combining logic with probabilities is a core idea to uncertain reasoning. Recently, approaches to probabilistic conditional logics based on first-order languages have been proposed that employ the principle of maximum entropy (ME), e.g. the logic FO-PCL. In order to simplify the ME model computation, FO-PCL knowledge bases can be transformed so that they become parametrically uniform. On the other hand, conditional structures have been proposed as a structural tool for investigating properties of conditional knowledge bases. In this paper, we present a software system for the computation, visualization, and comparison of conditional structures for relational probabilistic knowledge bases as they evolve in the transformation process that achieves parametric uniformity.
منابع مشابه
Generation of Parametrically Uniform Knowledge Bases in a Relational Probabilistic Logic with Maximum Entropy Semantics
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