diogo
/
yap-6.3
Archived
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

git learning stuff.

This commit is contained in:
Vitor Santos Costa 2009-03-09 00:40:50 +00:00
parent 1c87f3b41a
commit 620ac64fdd
2 changed files with 182 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

86
packages/ProbLog/problog_examples/graph.pl Normal file
View File

@ -0,0 +1,86 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% ProbLog program describing a probabilistic graph
% (running example from ProbLog presentations)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
:- use_module('../problog').
%%%%
% background knowledge
%%%%
% definition of acyclic path using list of visited nodes
path(X,Y) :- path(X,Y,[X],_).
path(X,X,A,A).
path(X,Y,A,R) :-
X\==Y,
edge(X,Z),
absent(Z,A),
path(Z,Y,[Z|A],R).
% using directed edges in both directions
edge(X,Y) :- dir_edge(Y,X).
edge(X,Y) :- dir_edge(X,Y).
% checking whether node hasn't been visited before
absent(_,[]).
absent(X,[Y|Z]):-X \= Y, absent(X,Z).
%%%%
% 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 path(1,4)
%
%%% explanation probability (and facts involved)
% ?- problog_max(path(1,4),Prob,FactsUsed).
% FactsUsed = [dir_edge(1,2),dir_edge(2,3),dir_edge(3,4)],
% Prob = 0.432 ?
% yes
%%% success probability
% ?- problog_exact(path(1,4),Prob,Status).
% 8 proofs
% Prob = 0.53864,
% Status = ok ?
% yes
%%% lower bound using 4 best proofs
% ?- problog_kbest(path(1,4),4,Prob,Status).
% 4 proofs
% Prob = 0.517344,
% 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
%%% upper and lower bound using iterative deepening, final interval width 0.01
% ?- problog_delta(path(1,4),0.01,Bound_low,Bound_up,Status).
% Bound_low = 0.5354096,
% Bound_up = 0.53864,
% Status = ok ?
% yes
%%% upper and lower bound obtained cutting the sld tree at probability 0.1 for each branch
% ?- problog_threshold(path(1,4),0.1,Bound_low,Bound_up,Status).
% 4 proofs
% Bound_low = 0.517344,
% Bound_up = 0.563728,
% Status = ok ?
% yes
%%% lower bound obtained cutting the sld tree at probability 0.2 for each branch
% ?- problog_low(path(1,4),0.2,Bound_low,Status).
% 1 proofs
% Bound_low = 0.432,
% Status = ok ?
% yes
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

96
packages/ProbLog/problog_examples/learn_graph.pl Normal file
View File

@ -0,0 +1,96 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% ProbLog program describing a probabilistic graph
% (running example from ProbLog presentations)
%
% example for parameter learning with LeProbLog
%
% training and test examples are included at the end of the file
%
% query ?- do_learning(20).
% will run 20 iterations of learning with default settings
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
:- use_module('../learning').
%%%%
% background knowledge
%%%%
% definition of acyclic path using list of visited nodes
path(X,Y) :- path(X,Y,[X],_).
path(X,X,A,A).
path(X,Y,A,R) :-
X\==Y,
edge(X,Z),
absent(Z,A),
path(Z,Y,[Z|A],R).
% using directed edges in both directions
edge(X,Y) :- dir_edge(Y,X).
edge(X,Y) :- dir_edge(X,Y).
% checking whether node hasn't been visited before
absent(_,[]).
absent(X,[Y|Z]):-X \= Y, absent(X,Z).
%%%%
% probabilistic facts
% - probability represented by t/1 term means learnable parameter
% - argument of t/1 is real value (used to compare against in evaluation when known), use t(_) if unknown
%%%%
t(0.9)::dir_edge(1,2).
t(0.8)::dir_edge(2,3).
t(0.6)::dir_edge(3,4).
t(0.7)::dir_edge(1,6).
t(0.5)::dir_edge(2,6).
t(0.4)::dir_edge(6,5).
t(0.7)::dir_edge(5,3).
t(0.2)::dir_edge(5,4).
%%%%%%%%%%%%%%
% training examples of form example(ID,Query,DesiredProbability)
%%%%%%%%%%%%%%
example(1,path(1,2),0.94).
example(2,path(1,3),0.81).
example(3,path(1,4),0.54).
example(4,path(1,5),0.70).
example(5,path(1,6),0.87).
example(6,path(2,3),0.85).
example(7,path(2,4),0.57).
example(8,path(2,5),0.72).
example(9,path(2,6),0.86).
example(10,path(3,4),0.66).
example(11,path(3,5),0.80).
example(12,path(3,6),0.75).
example(13,path(4,5),0.57).
example(14,path(4,6),0.51).
example(15,path(5,6),0.69).
% some examples for learning from proofs:
example(16,(dir_edge(2,3),dir_edge(2,6),dir_edge(6,5),dir_edge(5,4)),0.032).
example(17,(dir_edge(1,6),dir_edge(2,6),dir_edge(2,3),dir_edge(3,4)),0.168).
example(18,(dir_edge(5,3),dir_edge(5,4)),0.14).
example(19,(dir_edge(2,6),dir_edge(6,5)),0.2).
example(20,(dir_edge(1,2),dir_edge(2,3),dir_edge(3,4)),0.432).
%%%%%%%%%%%%%%
% test examples of form test_example(ID,Query,DesiredProbability)
% note: ID namespace is shared with training example IDs
%%%%%%%%%%%%%%
test_example(21,path(2,1),0.94).
test_example(22,path(3,1),0.81).
test_example(23,path(4,1),0.54).
test_example(24,path(5,1),0.70).
test_example(25,path(6,1),0.87).
test_example(26,path(3,2),0.85).
test_example(27,path(4,2),0.57).
test_example(28,path(5,2),0.72).
test_example(29,path(6,2),0.86).
test_example(30,path(4,3),0.66).
test_example(31,path(5,3),0.80).
test_example(32,path(6,3),0.75).
test_example(33,path(5,4),0.57).
test_example(34,path(6,4),0.51).
test_example(35,path(6,5),0.69).