Knowledge representation and inference in intelligent decision systems
Knowledge representation and inference in intelligent decision systems
Operations Research
Integrating model construction and evaluation
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Constructing Flexible Dynamic Belief Networks from First-Order Probalistic Knowledge Bases
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
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UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
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AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Network fragments: representing knowledge for constructing probabilistic models
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
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UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Stochastic lambda calculus and monads of probability distributions
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Using Bayesian Networks to Manage Uncertainty in Student Modeling
User Modeling and User-Adapted Interaction
Network Engineering for Agile Belief Network Models
IEEE Transactions on Knowledge and Data Engineering
Decision-model construction with multilevel influence diagrams
The Knowledge Engineering Review
A computational framework for package planning
International Journal of Knowledge-based and Intelligent Engineering Systems
MEBN: A language for first-order Bayesian knowledge bases
Artificial Intelligence
A knowledge-based modeling system for time-critical dynamic decision-making
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
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International Journal of Approximate Reasoning
Representing and combining partially specified CPTs
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Hypothesis management in situation-specific network construction
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
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This paper describes a process for constructing situation-specific belief networks from a knowledge base of network fragments. A situation-specific network is a minimal querycomplete network constructed from a knowledge base in response to a query for the probability distribution on a set of target variables given evidence and context variables. We present definitions of query completeness and situation-specific networks. We describe conditions on the knowledge base that guarantee query completeness. The relationship of our work to earlier work on KBMC is also discussed.