AbstractWe examine the representation of judgements of stochastic independence in probabilistic logics. We focus on a relational logic where (i) judgements of stochastic independence are encoded by directed acyclic graphs, and (ii) probabilistic assessments are flexible in the sense that they are not required to specify a single probability measure. We discuss issues of knowledge representation and inference that arise from our particular combination of graphs, stochastic independence, logical formulas and probabilistic assessments
AbstractWe propose a notion of conditional independence with respect to prepositional logic and stud...
The implication problem is to test whether a given set of independencies logically implies another i...
The semigraphoid closure of every couple of CI-statements (CI=conditional independence) is a stochas...
We examine the representation of judgements of stochastic independence in probabilistic logics. We f...
AbstractThis paper investigates probabilistic logics endowed with independence relations. We review ...
This paper investigates probabilistic logics endowed with independence relations. We review proposit...
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...
Independence and conditional independence are fundamental concepts for reasoning about groups of ran...
One of the goals of artificial intelligence is to develop agents that learn and act in complex envir...
A combinação de lógica e probabilidade (lógicas probabilísticas) tem sido um tópico bastante estudad...
The rules of d-separation provide a theoretical and algorithmic framework for deriving conditional i...
Bayesian networks are directed acyclic graphs representing independence relationships among a set of...
AbstractGraphs provide an excellent framework for interrogating symmetric models of measurement rand...
This paper investigates a representation language with flexibility inspired by probabilistic logic a...
AbstractWe propose a notion of conditional independence with respect to prepositional logic and stud...
The implication problem is to test whether a given set of independencies logically implies another i...
The semigraphoid closure of every couple of CI-statements (CI=conditional independence) is a stochas...
We examine the representation of judgements of stochastic independence in probabilistic logics. We f...
AbstractThis paper investigates probabilistic logics endowed with independence relations. We review ...
This paper investigates probabilistic logics endowed with independence relations. We review proposit...
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...
Independence and conditional independence are fundamental concepts for reasoning about groups of ran...
One of the goals of artificial intelligence is to develop agents that learn and act in complex envir...
A combinação de lógica e probabilidade (lógicas probabilísticas) tem sido um tópico bastante estudad...
The rules of d-separation provide a theoretical and algorithmic framework for deriving conditional i...
Bayesian networks are directed acyclic graphs representing independence relationships among a set of...
AbstractGraphs provide an excellent framework for interrogating symmetric models of measurement rand...
This paper investigates a representation language with flexibility inspired by probabilistic logic a...
AbstractWe propose a notion of conditional independence with respect to prepositional logic and stud...
The implication problem is to test whether a given set of independencies logically implies another i...
The semigraphoid closure of every couple of CI-statements (CI=conditional independence) is a stochas...