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Answering Queries from Context-Sensitive Probabilistic Knowledge Bases
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Anytime Deduction for Probabilistic Logic
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A comparative analysis of techniques for predicting academic performance
TLDR
In this analysis, the decision tree was consistently 3-12% more accurate than the Bayesian network for predicting student performance, and the maturity of open source tools was demonstrated.
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Generating Bayesian Networks from Probablity Logic Knowledge Bases
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Utility Models for Goal‐Directed, Decision‐Theoretic Planners
TLDR
AI planning agents are goal‐directed: success is measured in terms of whether an input goal is satisfied, and planning representations and algorithms have been designed to exploit that structure.
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Intelligent dental training simulator with objective skill assessment and feedback
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Construction of a Bayesian network for mammographic diagnosis of breast cancer.
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Decision-theoretic Refinement Planning Using Inheritance Abstraction
TLDR
Tenenberg’s notion of inheritance abstraction for STRIPS operators to apply to conditional probabilistic actions is extended and the intent is to formalize the notion that analogous action types can be structured together into an action class at the abstract level.
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Probabilistic Logic Programming and Bayesian Networks
TLDR
This work defines a fixpoint theory, declarative semantics, and proof procedure for the new class of probabilistic logic programs, and discusses the relationship between such programs and Bayesian networks, thus moving toward a unification of two major approaches to automated reasoning.
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A bibliometric study of the world’s research activity in sustainable development and its sub-areas using scientific literature
TLDR
The results indicate that institutes strong in Sustainable Development overall may not be strong in all sub-areas and that institute not strong in sustainable development overall may have significant niche strengths in a given sub-area.
View on Springer
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