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