Titlebook: Symbolic and Quantitative Approaches to Reasoning with Uncertainty; 15th European Confer Gabriele Kern-Isberner,Zoran Ognjanovi? Conference

木訥

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/t/image/883849.jpg

外觀

https://doi.org/10.1007/978-3-030-29765-7argumentation; argumentation frameworks; artificial intelligence; bayesian networks; formal logic; knowle

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Intellectual

A Model-Based Theorem Prover for Epistemic Graphs for Argumentationss which offers computational benefits while still being powerful enough to allow for handling of many other argumentation formalisms and that can be used in applications that, for instance, rely on Likert scales. In this paper, we propose a model-based theorem prover for reasoning with the restricted epistemic language.

盟軍

Constructing Bayesian Network Graphs from Labeled Argumentsnces may not be causal, we generalize this approach to include other types of inferences in this paper. Moreover, we prove a number of formal properties of the generalized approach and identify assumptions under which the construction of an initial BN graph can be fully automated.

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蓋他為秘密