This paper investigates probabilistic logics endowed with independence relations. We review propositional probabilistic languages without independence, and then consider graph-theoretic representations for propositional probabilistic logic with independence; complexity is analyzed, algorithms are derived, and examples are discussed. Finally, we examine a restricted rst order probabilistic logic that gener-alizes relational Bayesian networks
A significant part of current research on (inductive) logic programming deals with probabilistic log...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
This paper investigates a representation language with flexibility inspired by probabilistic logic a...
AbstractThis paper investigates probabilistic logics endowed with independence relations. We review ...
This paper investigates probabilistic logics endowed with independence relations. We review proposit...
\u3cp\u3eThis papers investigates the manipulation of statements of strong independence in probabili...
We examine the representation of judgements of stochastic independence in probabilistic logics. We f...
AbstractWe examine the representation of judgements of stochastic independence in probabilistic logi...
A logical concept of representation independence is developed for nonmonotonic logics, including pr...
We consider the problem of learning conditional independencies, ex-pressed as a Markov network, from...
Bayesian networks are directed acyclic graphs representing independence relationships among a set of...
Probabilistic graphical models, such as Bayesian networks, allow representing conditional independen...
Probabilistic logics have attracted a great deal of attention during the past few years. Where logic...
We study the expressivity and the complexity of various logics in probabilistic team semantics with ...
AbstractThis paper offers an axiomatic characterization of the probabilistic relation “X is independ...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
This paper investigates a representation language with flexibility inspired by probabilistic logic a...
AbstractThis paper investigates probabilistic logics endowed with independence relations. We review ...
This paper investigates probabilistic logics endowed with independence relations. We review proposit...
\u3cp\u3eThis papers investigates the manipulation of statements of strong independence in probabili...
We examine the representation of judgements of stochastic independence in probabilistic logics. We f...
AbstractWe examine the representation of judgements of stochastic independence in probabilistic logi...
A logical concept of representation independence is developed for nonmonotonic logics, including pr...
We consider the problem of learning conditional independencies, ex-pressed as a Markov network, from...
Bayesian networks are directed acyclic graphs representing independence relationships among a set of...
Probabilistic graphical models, such as Bayesian networks, allow representing conditional independen...
Probabilistic logics have attracted a great deal of attention during the past few years. Where logic...
We study the expressivity and the complexity of various logics in probabilistic team semantics with ...
AbstractThis paper offers an axiomatic characterization of the probabilistic relation “X is independ...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
This paper investigates a representation language with flexibility inspired by probabilistic logic a...