Conditional Probabilistic Event Logic is a probabilistic modeling language, which allows explicit representations of causal processes. Syntactically, this logic bears a strong resemblance to the probabilistic logic programming language of Logic Programming with Annotated Disjunctions. In this paper, we investigate the relation between the semantics of these two languages and prove an equivalence result for a certain class of theories. This result exposes an interesting relation between the well-founded semantics for logic programs and causal reasoning.nrpages: 10status: publishe
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...
A multitude of different probabilistic programming languages exists today, all extending a tradition...
This papers develops a logical language for representing probabilistic causal laws. Our interest ...
This papers develops a logical language for representing probabilistic causal laws. Our interest in ...
We study causal information about probabilistic processes, i.e., information about why events occur....
There is a growing interest in languages that combine probabilistic models with logic to represent c...
AbstractOf all scientific investigations into reasoning with uncertainty and chance, probability the...
Constructive processes play an important role in knowledge representation. Indeed, there are many f...
Constructive processes (i.e., derivations which gradually build up a model of the world) play an imp...
The action language C+ is an important high-level formalism for describing actions, which has evolv...
We examine the vexed question of connections between logical and probabilistic reasoning. The reason...
We examine the vexed question of connections between logical and probabilistic reasoning. The reason...
We propose a formalization of the three-tier causal hierarchy of association, intervention, and coun...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
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...
A multitude of different probabilistic programming languages exists today, all extending a tradition...
This papers develops a logical language for representing probabilistic causal laws. Our interest ...
This papers develops a logical language for representing probabilistic causal laws. Our interest in ...
We study causal information about probabilistic processes, i.e., information about why events occur....
There is a growing interest in languages that combine probabilistic models with logic to represent c...
AbstractOf all scientific investigations into reasoning with uncertainty and chance, probability the...
Constructive processes play an important role in knowledge representation. Indeed, there are many f...
Constructive processes (i.e., derivations which gradually build up a model of the world) play an imp...
The action language C+ is an important high-level formalism for describing actions, which has evolv...
We examine the vexed question of connections between logical and probabilistic reasoning. The reason...
We examine the vexed question of connections between logical and probabilistic reasoning. The reason...
We propose a formalization of the three-tier causal hierarchy of association, intervention, and coun...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
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...
A multitude of different probabilistic programming languages exists today, all extending a tradition...