Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
Anti-unification in constraint logics: foundations and applications to learnability in first-order logic, to speed-up learning, and to deduction
ACM SIGKDD Explorations Newsletter
Adaptive Bayesian Logic Programs
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Towards Combining Inductive Logic Programming with Bayesian Networks
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Learning probabilities for noisy first-order rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Parameter learning of logic programs for symbolic-statistical modeling
Journal of Artificial Intelligence Research
ACM SIGKDD Explorations Newsletter
PRL: A probabilistic relational language
Machine Learning
Machine Learning
Quantitative pharmacophore models with inductive logic programming
Machine Learning
Reasoning with recursive loops under the PLP framework
ACM Transactions on Computational Logic (TOCL)
Learning to assign degrees of belief in relational domains
Machine Learning
Structured machine learning: the next ten years
Machine Learning
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
On the Efficient Execution of ProbLog Programs
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Probabilistic reasoning with answer sets
Theory and Practice of Logic Programming
An Inductive Logic Programming Approach to Statistical Relational Learning
Proceedings of the 2005 conference on An Inductive Logic Programming Approach to Statistical Relational Learning
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Cp-logic: A language of causal probabilistic events and its relation to logic programming
Theory and Practice of Logic Programming
View learning for statistical relational learning: with an application to mammography
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Logic–based decision support for strategic environmental assessment
Theory and Practice of Logic Programming
SLGAD Resolution for Inference on Logic Programs with Annotated Disjunctions
Fundamenta Informaticae - RCRA 2008 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
On the implementation of the probabilistic logic programming language problog
Theory and Practice of Logic Programming
Adaptive dialogue strategy selection through imprecise probabilistic query answering
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Probabilistic space partitioning in constraint logic programming
ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
PFORTE: revising probabilistic FOL theories
IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
On the implementation of the CLP(BN) language
PADL'10 Proceedings of the 12th international conference on Practical Aspects of Declarative Languages
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Logical bayesian networks and their relation to other probabilistic logical models
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Probabilistic first-order theory revision from examples
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Imprecise probabilistic query answering using measures of ignorance and degree of satisfaction
Annals of Mathematics and Artificial Intelligence
Model checking with probabilistic tabled logic programming
Theory and Practice of Logic Programming
Inference for a new probabilistic constraint logic
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In Datalog, missing values are represented by Skolem constants. More generally, in logic programming missing values, or existentially-quantified variables, are represented by terms built from Skolem functors. In an analogy to probabilistic relational models (PRMs), we wish to represent the joint probability distribution over missing values in a database or logic program using a Bayesian network. This paper presents an extension of logic programs that makes it possible to specify a joint probability distribution over terms built from Skolem functors in the program. Our extension is based on constraint logic programming (CLP), so we call the extended language CLP(BN). We show that CLP(BN) subsumes PRMs; this greater expressivity carries both advantages and disadvantages for CLP(BN). We also show that algorithms from inductive logic programming (ILP) can be used with only minor modification to learn CLP(BN) programs. An implementation of CLP(BN) is publicly available as part of YAP Prolog at http://www.cos.ufrj.br/~vitor/Yap/clpbn