This paper investigates probabilistic logics endowed with independence relations. We review propositional probabilistic languages without and with independence. We 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 first-order probabilistic logic that generalizes relational Bayesian networks. (c) 2007 Elsevier Inc. All rights reserved
AbstractThis paper offers an axiomatic characterization of the probabilistic relation “X is independ...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
We study the expressivity and the complexity of various logics in probabilistic team semantics with ...
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...
Probabilistic graphical models, such as Bayesian networks, allow representing conditional independen...
A logical concept of representation independence is developed for nonmonotonic logics, including pr...
Bayesian networks are directed acyclic graphs representing independence relationships among a set of...
Probabilistic logics have attracted a great deal of attention during the past few years. Where logic...
We consider the problem of learning conditional independencies, ex-pressed as a Markov network, from...
Abstract This paper discuses multiple Bayesian networks representation paradigms for encoding asymme...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
AbstractThis paper offers an axiomatic characterization of the probabilistic relation “X is independ...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
We study the expressivity and the complexity of various logics in probabilistic team semantics with ...
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...
Probabilistic graphical models, such as Bayesian networks, allow representing conditional independen...
A logical concept of representation independence is developed for nonmonotonic logics, including pr...
Bayesian networks are directed acyclic graphs representing independence relationships among a set of...
Probabilistic logics have attracted a great deal of attention during the past few years. Where logic...
We consider the problem of learning conditional independencies, ex-pressed as a Markov network, from...
Abstract This paper discuses multiple Bayesian networks representation paradigms for encoding asymme...
A significant part of current research on (inductive) logic programming deals with probabilistic log...
AbstractThis paper offers an axiomatic characterization of the probabilistic relation “X is independ...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
We study the expressivity and the complexity of various logics in probabilistic team semantics with ...