Add to ORKGIn recent years, there has been a significant interest in integrating probability theory with first order logic and relational representations [see De Raedt and Kersting, 2003, for an overview]. Muggleton [1996] and Cussens [1999] have upgraded stochastic grammars towards Stochastic Logic Programs, Sato and Kameya [2001
This talk consists of two parts. In the first part we analyze Bayesian Logic Programs from a knowled...
We review Logical Bayesian Networks, a language for probabilistic logical modelling, and discuss its...
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
First-order probabilistic models are recognized as efficient frameworks to represent several realwor...
Abstract. This paper presents a revised comparison of Bayesian logic programs (BLPs) and stochastic ...
© Springer-Verlag Berlin Heidelberg 2001. First order probabilistic logics combine a first order log...
I examine the idea of incorporating probability into logic for a logic of practical reasoning. I int...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
© Springer-Verlag Berlin Heidelberg 2001. Recently, new representation languages that integrate firs...
Uncertainty is a fundamental and irreducible aspect of our knowledge about the world. Until recently...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
Probabilistic logics have attracted a great deal of attention during the past few years. Where logic...
Uncertainty is a fundamental and irreducible aspect of our knowledge about the world. Probability is...
This chapter offers an accessible introduction to the channel-based approach to Bayesian probability...
This talk consists of two parts. In the first part we analyze Bayesian Logic Programs from a knowled...
We review Logical Bayesian Networks, a language for probabilistic logical modelling, and discuss its...
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
First-order probabilistic models are recognized as efficient frameworks to represent several realwor...
Abstract. This paper presents a revised comparison of Bayesian logic programs (BLPs) and stochastic ...
© Springer-Verlag Berlin Heidelberg 2001. First order probabilistic logics combine a first order log...
I examine the idea of incorporating probability into logic for a logic of practical reasoning. I int...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
© Springer-Verlag Berlin Heidelberg 2001. Recently, new representation languages that integrate firs...
Uncertainty is a fundamental and irreducible aspect of our knowledge about the world. Until recently...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
Probabilistic logics have attracted a great deal of attention during the past few years. Where logic...
Uncertainty is a fundamental and irreducible aspect of our knowledge about the world. Probability is...
This chapter offers an accessible introduction to the channel-based approach to Bayesian probability...
This talk consists of two parts. In the first part we analyze Bayesian Logic Programs from a knowled...
We review Logical Bayesian Networks, a language for probabilistic logical modelling, and discuss its...
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational...