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PFL manual: improve introduction section

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Tiago Gomes 2013-01-08 19:40:20 +00:00
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packages/CLPBN/pfl.tex
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\section{Introduction}
The Prolog Factor Language (PFL) is a extension of the Prolog language that allows a natural representation of this first-order probabilistic models (either directed or undirected). PFL is also capable of solving probabilistic queries on this models through the implementation of several inference techniques: variable elimination, belief propagation, lifted variable elimination and lifted belief propagation.
The Prolog Factor Language (PFL) is a language that extends Prolog for providing a syntax to describe first-order probabilistic graphical models. These models can be either directed (bayesian networks) or undirected (markov networks). This language replaces the old one known as CLP($\mathcal{BN}$).
The package also includes implementations for a set of well-known inference algorithms for solving probabilistic queries on these models. Both ground and lifted inference methods are support.
\section{Installation}
PFL is included with the \href{http://www.dcc.fc.up.pt/~vsc/Yap/}{YAP} Prolog system. However, there isn't yet a stable release of YAP that includes PFL. So it is required to install a development version of YAP. To to this, you will need to have installed the Git version control system. The commands to do a default installation of YAP in the user's home in a Unix-based environment are shown next.