By Thierry Denœux (auth.), Khaled Mellouli (eds.)
This ebook constitutes the refereed lawsuits of the ninth eu convention on Symbolic and Quantitative methods to Reasoning with Uncertainty, ECSQARU 2007, held in Hammammet, Tunisia, October 2007.
The seventy eight revised complete papers awarded including 3 invited papers have been conscientiously reviewed and chosen from over 100 submissions for inclusion within the ebook. The papers are geared up in topical sections on Bayesian networks, graphical versions, studying causal networks, making plans, causality and independence, choice modeling and selection, argumentation platforms, inconsistency dealing with, trust revision and merging, trust features, fuzzy types, many-valued logical platforms, uncertainty logics, probabilistic reasoning, reasoning versions lower than uncertainty, uncertainty measures, probabilistic classifiers, type and clustering, and commercial applications.
Read Online or Download Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 9th European Conference, ECSQARU 2007, Hammamet, Tunisia, October 31 - November 2, 2007. Proceedings PDF
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Additional info for Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 9th European Conference, ECSQARU 2007, Hammamet, Tunisia, October 31 - November 2, 2007. Proceedings
Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoritic Approach. , Domingo-Ferrer, J. ) MDAI 2006. LNCS (LNAI), vol. 3885, pp. 58–69. Springer, Heidelberg (2006) 16. : Active Learning of Causal Bayes Net Structure. Technical report, Department of Computer Science, UC Berkeley (2001) 17. : Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Francisco (1988) 18. : Causality: Models, Reasoning and Inference. Cambridge University Press, Cambridge (2000) 19.
Furthermore, measuring inconsistency in a knowledge base in classical logic can provide some context information which can be used to resolve inconsistency [6,7,8]. org/), and by the Deutsche Forschungsgemeinschaft (DFG) in the ReaSem project. K. ): ECSQARU 2007, LNAI 4724, pp. 30–41, 2007. c Springer-Verlag Berlin Heidelberg 2007 Measuring Inconsistency for Description Logics Based on Paraconsistent Semantics 31 There are mainly two classes of inconsistency measures in classical logic. e. a knowledge base in propositional logic is more inconsistent if more logical formulas are required to produce the inconsistency .
Is a model of it) iff it satisfies each assertion and each inclusion axiom in KB. A knowledge base KB is 4-valued satisfiable (unsatisfiable) iff there exists (does not exist) such a model. 3 Domain-Dependent Inconsistency In this section, we define a domain-dependent inconsistency in DLs. We first recall the notion of inconsistency in DLs. Measuring Inconsistency for Description Logics Based on Paraconsistent Semantics 35 Definition 2. A knowledge base KB is classically inconsistent iff KB has no classical model.
Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 9th European Conference, ECSQARU 2007, Hammamet, Tunisia, October 31 - November 2, 2007. Proceedings by Thierry Denœux (auth.), Khaled Mellouli (eds.)