Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Representations of commonsense knowledge
Representations of commonsense knowledge
An analysis of first-order logics of probability
Artificial Intelligence
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Local expression languages for probabilistic dependence: a preliminary report
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
Advances in probabilistic reasoning
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
A Bayesian model of plan recognition
Artificial Intelligence
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
International Journal of Human-Computer Studies - Special issue: real-world applications of uncertain reasoning
From statistical knowledge bases to degrees of belief
Artificial Intelligence
Answering queries from context-sensitive probabilistic knowledge bases
Selected papers from the international workshop on Uncertainty in databases and deductive systems
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Bayesian Multiple Target Tracking
Bayesian Multiple Target Tracking
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Complex Probabilistic Modeling with Recursive Relational Bayesian Networks
Annals of Mathematics and Artificial Intelligence
Learning Probabilistic Relational Models
SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
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
Structural Learning in Object Oriented Domains
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference
Hypothesis Management in Situation-Specific Network Construction
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Learning Dynamic Bayesian Networks
Adaptive Processing of Sequences and Data Structures, International Summer School on Neural Networks, "E.R. Caianiello"-Tutorial Lectures
Evidential Reasoning for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fusion of domain knowledge with data for structural learning in object oriented domains
The Journal of Machine Learning Research
ACM SIGKDD Explorations Newsletter
Learning first-order probabilistic models with combining rules
ICML '05 Proceedings of the 22nd international conference on Machine learning
Learning Bayesian Networks
Operations for learning with graphical models
Journal of Artificial Intelligence Research
First-order probabilistic inference
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
BLOG: probabilistic models with unknown objects
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Representing and combining partially specified CPTs
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Constructing situation specific belief networks
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Object-oriented Bayesian networks
UAI'97 Proceedings of the Thirteenth 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
Computational advantages of relevance reasoning in Bayesian belief networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Semantic Science: Ontologies, Data and Probabilistic Theories
Uncertainty Reasoning for the Semantic Web I
PR-OWL: A Bayesian Ontology Language for the Semantic Web
Uncertainty Reasoning for the Semantic Web I
Learning first-order probabilistic models with combining rules
Annals of Mathematics and Artificial Intelligence
Automated compilation of Object-Oriented Probabilistic Relational Models
International Journal of Approximate Reasoning
Equipping robot control programs with first-order probabilistic reasoning capabilities
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Probabilistic categorization of kitchen objects in table settings with a composite sensor
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
The role of service oriented architectures in systems engineering
Information-Knowledge-Systems Management
Probabilistic Ontologies for Multi-INT Fusion
Proceedings of the 2010 conference on Ontologies and Semantic Technologies for Intelligence
Fusing multiple Bayesian knowledge sources
International Journal of Approximate Reasoning
Chameleon: a model of identification, authorization and accountability for ubicomp
UIC'11 Proceedings of the 8th international conference on Ubiquitous intelligence and computing
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
On the combination of logical and probabilistic models for information analysis
Applied Intelligence
Structured probabilistic inference
International Journal of Approximate Reasoning
Probabilistic model-based assessment of information quality in uncertain domains
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
KnowRob: A knowledge processing infrastructure for cognition-enabled robots
International Journal of Robotics Research
State-of-the-art of intention recognition and its use in decision making
AI Communications
Intelligent Decision Technologies
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Although classical first-order logic is the de facto standard logical foundation for artificial intelligence, the lack of a built-in, semantically grounded capability for reasoning under uncertainty renders it inadequate for many important classes of problems. Probability is the best-understood and most widely applied formalism for computational scientific reasoning under uncertainty. Increasingly expressive languages are emerging for which the fundamental logical basis is probability. This paper presents Multi-Entity Bayesian Networks (MEBN), a first-order language for specifying probabilistic knowledge bases as parameterized fragments of Bayesian networks. MEBN fragments (MFrags) can be instantiated and combined to form arbitrarily complex graphical probability models. An MFrag represents probabilistic relationships among a conceptually meaningful group of uncertain hypotheses. Thus, MEBN facilitates representation of knowledge at a natural level of granularity. The semantics of MEBN assigns a probability distribution over interpretations of an associated classical first-order theory on a finite or countably infinite domain. Bayesian inference provides both a proof theory for combining prior knowledge with observations, and a learning theory for refining a representation as evidence accrues. A proof is given that MEBN can represent a probability distribution on interpretations of any finitely axiomatizable first-order theory.