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yap-6.3/packages/ProbLog/problog_examples/graph_tabled.pl

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2010-08-26 13:44:10 +01:00
%%% -*- Mode: Prolog; -*-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% ProbLog program describing a probabilistic graph using tabling
% (running example from ProbLog presentations)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
:- use_module('../problog').
% New trie method ensures Probibilistic Cycle Handling needed for tabling that handles loops
:- set_problog_flag(use_db_trie, true).
:- set_problog_flag(use_old_trie, false).
%%%%
% background knowledge
%%%%
% definition of acyclic path using list of visited nodes
% to table a predicate you first need to define it as a dynamic one
:- dynamic path/2.
path(X,X).
path(X,Y) :-
X\==Y,
edge(X,Z),
path(Z,Y).
:- problog_table path/2.
% after all predicate definitions have appeared you need to state that the predicate will be tabled
% using directed edges in both directions
edge(X,Y) :- dir_edge(Y,X).
edge(X,Y) :- dir_edge(X,Y).
%%%%
% probabilistic facts
%%%%
0.9::dir_edge(1,2).
0.8::dir_edge(2,3).
0.6::dir_edge(3,4).
0.7::dir_edge(1,6).
0.5::dir_edge(2,6).
0.4::dir_edge(6,5).
0.7::dir_edge(5,3).
0.2::dir_edge(5,4).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% example queries about tabled path(1,4) useable only with problog_exact, problog_montecarlo currently
%
%%% success probability
% ?- problog_exact(path(1,4),Prob,Status).
% Prob = 0.53864,
% Status = ok ?
% yes
%%% approximation using monte carlo, to reach 95%-confidence interval width 0.01
% ?- problog_montecarlo(path(1,4),0.01,Prob).
% Prob = 0.537525 ?
% yes
%%% success probability of negation
% ?- problog_exact(problog_neg(path(1,4)),Prob,Status).
% Prob = 0.46136,
% Status = ok ?
% yes
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%