Probabilistic Horn abduction is a simple framework to combine probabilistic and logical reasoning into a coherent practical framework. The numbers can be consistently interpreted probabilistically, and all of the rules can be interpreted logically. The relationship between probabilistic Horn abduction and logic programming is at two levels. At the first level probabilistic Horn abduction is an extension of pure Prolog, that is useful for diagnosis and other evidential reasoning tasks. At another level, current logic programming implementation techniques can be used to efficiently implement probabilistic Horn abduction. This forms the basis of an "anytime" algorithm for estimating arbitrary conditional probabilities. The focus of t...
Probabilistic Logic Programming (PLP) has come to the fore in the last decades as one of the most pr...
© 2016 Elsevier Inc. We propose T P -compilation, a new inference technique for probabilistic logic...
Probabilistic programs combine the power of programming languages with that of probabilistic graphic...
Probabilistic Horn abduction is a simple framework to combine probabilistic and logical reasoning in...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
A multitude of different probabilistic programming languages exists today, all extending a tradition...
This paper proposes and investigates an approach to deduction in probabilistic logic, using as its m...
A multitude of different probabilistic programming languages exists today, all extending a tradition...
In Probabilistic Abductive Logic Programming we are given a probabilistic logic program, a set of ab...
Probabilistic logic learning (PLL), sometimes also called statistical relational learning, addresses...
We present a new approach to probabilistic logic programs with a possible worlds semantics. Classica...
A multitude of different probabilistic programming languages exists to-day, all extending a traditio...
Probabilistic programming is an emerging subfield of AI that extends traditional programming languag...
We introduce a new approach to probabilistic logic programming in which probabilities are defined ov...
AbstractWe study two basic problems of probabilistic reasoning: the probabilistic logic and the prob...
Probabilistic Logic Programming (PLP) has come to the fore in the last decades as one of the most pr...
© 2016 Elsevier Inc. We propose T P -compilation, a new inference technique for probabilistic logic...
Probabilistic programs combine the power of programming languages with that of probabilistic graphic...
Probabilistic Horn abduction is a simple framework to combine probabilistic and logical reasoning in...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
A multitude of different probabilistic programming languages exists today, all extending a tradition...
This paper proposes and investigates an approach to deduction in probabilistic logic, using as its m...
A multitude of different probabilistic programming languages exists today, all extending a tradition...
In Probabilistic Abductive Logic Programming we are given a probabilistic logic program, a set of ab...
Probabilistic logic learning (PLL), sometimes also called statistical relational learning, addresses...
We present a new approach to probabilistic logic programs with a possible worlds semantics. Classica...
A multitude of different probabilistic programming languages exists to-day, all extending a traditio...
Probabilistic programming is an emerging subfield of AI that extends traditional programming languag...
We introduce a new approach to probabilistic logic programming in which probabilities are defined ov...
AbstractWe study two basic problems of probabilistic reasoning: the probabilistic logic and the prob...
Probabilistic Logic Programming (PLP) has come to the fore in the last decades as one of the most pr...
© 2016 Elsevier Inc. We propose T P -compilation, a new inference technique for probabilistic logic...
Probabilistic programs combine the power of programming languages with that of probabilistic graphic...