2014-08-06 16:26:03 +01:00
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%%% -*- mode: Prolog; -*-
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2012-04-27 16:30:02 +01:00
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% ProbLog program describing a probabilistic graph
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% (running example from ProbLog presentations)
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% $Id: learn_graph.pl 4875 2010-10-05 15:28:35Z theo $
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% example for parameter learning with LeProbLog
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%
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% training and test examples are included at the end of the file
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% query ?- do_learning(20).
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% will run 20 iterations of learning with default settings
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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2015-02-17 20:26:46 +00:00
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:- use_module(library(problog_lbdd)).
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2012-04-27 16:30:02 +01:00
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:- use_module(library(problog_learning_lbdd)).
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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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path(X,Y) :- path(X,Y,[X],_).
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path(X,X,A,A).
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path(X,Y,A,R) :-
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X\==Y,
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edge(X,Z),
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absent(Z,A),
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path(Z,Y,[Z|A],R).
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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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% checking whether node hasn't been visited before
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absent(_,[]).
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absent(X,[Y|Z]):-X \= Y, absent(X,Z).
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%%%%
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% probabilistic facts
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% - probability represented by t/1 term means learnable parameter
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% - argument of t/1 is real value (used to compare against in evaluation when known), use t(_) if unknown
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%%%%
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t(0.9)::dir_edge(1,2).
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t(0.8)::dir_edge(2,3).
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t(0.6)::dir_edge(3,4).
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t(0.7)::dir_edge(1,6).
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t(0.5)::dir_edge(2,6).
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t(0.4)::dir_edge(6,5).
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t(0.7)::dir_edge(5,3).
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t(0.2)::dir_edge(5,4).
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%%%%%%%%%%%%%%
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% training examples of form example(ID,Query,DesiredProbability)
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%%%%%%%%%%%%%%
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example(1,path(1,2),0.94).
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example(2,path(1,3),0.81).
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example(3,path(1,4),0.54).
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example(4,path(1,5),0.70).
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example(5,path(1,6),0.87).
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example(6,path(2,3),0.85).
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example(7,path(2,4),0.57).
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example(8,path(2,5),0.72).
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example(9,path(2,6),0.86).
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example(10,path(3,4),0.66).
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example(11,path(3,5),0.80).
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example(12,path(3,6),0.75).
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example(13,path(4,5),0.57).
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example(14,path(4,6),0.51).
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example(15,path(5,6),0.69).
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% some examples for learning from proofs:
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example(16,(dir_edge(2,3),dir_edge(2,6),dir_edge(6,5),dir_edge(5,4)),0.032).
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example(17,(dir_edge(1,6),dir_edge(2,6),dir_edge(2,3),dir_edge(3,4)),0.168).
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example(18,(dir_edge(5,3),dir_edge(5,4)),0.14).
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example(19,(dir_edge(2,6),dir_edge(6,5)),0.2).
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example(20,(dir_edge(1,2),dir_edge(2,3),dir_edge(3,4)),0.432).
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%%%%%%%%%%%%%%
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% test examples of form test_example(ID,Query,DesiredProbability)
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% note: ID namespace is shared with training example IDs
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%%%%%%%%%%%%%%
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test_example(21,path(2,1),0.94).
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test_example(22,path(3,1),0.81).
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test_example(23,path(4,1),0.54).
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test_example(24,path(5,1),0.70).
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test_example(25,path(6,1),0.87).
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test_example(26,path(3,2),0.85).
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test_example(27,path(4,2),0.57).
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test_example(28,path(5,2),0.72).
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test_example(29,path(6,2),0.86).
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test_example(30,path(4,3),0.66).
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test_example(31,path(5,3),0.80).
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test_example(32,path(6,3),0.75).
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test_example(33,path(5,4),0.57).
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test_example(34,path(6,4),0.51).
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test_example(35,path(6,5),0.69).
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