|Title:||Bayesian Logic Programs.|
|Authors:||Luc de Raedt and Kristian Kersting|
|Series:||Linköping Electronic Articles in Computer and Information Science|
|Issue:||Vol. 5 (2000): nr 034|
Bayesian networks provide an elegant formalism for representing and
reasoning about uncertainty. They
are a probabilistic extension of propositional logic and, hence, inherit
some of the limitations of propositional logic, such as the difficulties
to represent objects and relations.
The main contribution of this extended abstract is to
introduce a new approach, called Bayesian logic programs, to overcome
It combines Bayesian networks with definite clause logic, i.e. "pure"
establishing a one-to-one mapping between ground atoms and
random variables. Thus, Bayesian logic programs combine
the advantages of definite clause logic and Bayesian networks.
This includes the separation of quantitative and qualitative aspects
of the world.
Furthermore, Bayesian logic programs generalize both Bayesian networks
as well as
logic programs, many ideas developed in both areas can be adapted.
|Info from authors|