Add to ORKGThe concept of “probabilistic logic ” known in artificial intelligence needs a more thorough substantiation. A new approach to constructing probabilistic logic based on the N-tuple algebra developed by the author is proposed. A brief introduction is given to the N-tuple algebra and its properties that provide efficient paralleling of algorithms for solving problems of logical analysis of systems in computer implementation are generalized. Methods for solving direct and inverse problems of probabilistic simulation of logical systems are considered
Abstract. Probabilistic inductive logic programming, sometimes also called statistical relational le...
Abstract. Probabilistic inductive logic programming, sometimes also called statistical relational le...
Probabilistic logics combine the expressive power of logic with the ability to reason with uncertain...
We present a new approach to probabilistic logic programs with a possible worlds semantics. Classica...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
Probabilistic logic learning (PLL), sometimes also called statistical relational learning, addresses...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
We introduce a new approach to probabilistic logic programming in which probabilities are defined ov...
This thesis provides an algebraic modelling and verification of probabilistic concurrent systems in ...
Probabilistic Logic and Probabilistic Networks presents a groundbreaking framework within which vari...
The paper examines the usage potential of n-tuple algebra (NTA) developed by the authors as a theore...
Theoretical thesis.Bibliography: pages 167-175.1. Introduction -- 2. Continuity in probabilistic Kle...
AbstractProbability is usually closely related to Boolean structures, i.e., Boolean algebras or prop...
Abstract Probabilistic logics combine the expressive power of logic with the ability to reason with ...
Probabilistic logics combine the expressive power of logic with the ability to reason with uncertain...
Abstract. Probabilistic inductive logic programming, sometimes also called statistical relational le...
Abstract. Probabilistic inductive logic programming, sometimes also called statistical relational le...
Probabilistic logics combine the expressive power of logic with the ability to reason with uncertain...
We present a new approach to probabilistic logic programs with a possible worlds semantics. Classica...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
Probabilistic logic learning (PLL), sometimes also called statistical relational learning, addresses...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
We introduce a new approach to probabilistic logic programming in which probabilities are defined ov...
This thesis provides an algebraic modelling and verification of probabilistic concurrent systems in ...
Probabilistic Logic and Probabilistic Networks presents a groundbreaking framework within which vari...
The paper examines the usage potential of n-tuple algebra (NTA) developed by the authors as a theore...
Theoretical thesis.Bibliography: pages 167-175.1. Introduction -- 2. Continuity in probabilistic Kle...
AbstractProbability is usually closely related to Boolean structures, i.e., Boolean algebras or prop...
Abstract Probabilistic logics combine the expressive power of logic with the ability to reason with ...
Probabilistic logics combine the expressive power of logic with the ability to reason with uncertain...
Abstract. Probabilistic inductive logic programming, sometimes also called statistical relational le...
Abstract. Probabilistic inductive logic programming, sometimes also called statistical relational le...
Probabilistic logics combine the expressive power of logic with the ability to reason with uncertain...