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Merge branch 'master' of https://github.com/tacgomes/yap6.3

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Conflicts:
	packages/CLPBN/clpbn/horus.yap
This commit is contained in:
Vitor Santos Costa
2012-06-04 16:29:56 +01:00
parent 1fbd5c268b eec4b1452b
commit 3669cb894f
139 changed files with 9203 additions and 7699 deletions
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25
packages/CLPBN/examples/City/db_128.yap
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%conservative_city(nyc, t).
hair_color(joe, t).
car_color(joe, t).
shoe_size(joe, f).
/* Steps:
1. generate N facts lives(I, nyc), 0 <= I < N.
2. generate evidence on descn for N people, *** except for 1 ***
3. Run query ?- guilty(joe, Guilty), witness(joe, t), descn(2,t), descn(3, f), descn(4, f).
query(Guilty) :-
guilty(joe, Guilty),
witness(joe, t),
descn(2,t),
descn(3,f),
descn(4,f), ....
*/

60
packages/CLPBN/examples/City/schema.yap
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/* base file for school database. Supposed to be called from school_*.yap */
conservative_city(City, Cons) :-
cons_table(City, ConsDist),
{ Cons = cons(City) with p([y,n], ConsDist) }.
gender(X, Gender) :-
gender_table(City, GenderDist),
{ Gender = gender(City) with p([m,f], GenderDist) }.
hair_color(X, Color) :-
lives(X, City),
conservative_city(City, Cons),
gender(X, Gender),
color_table(X,ColorTable),
{ Color = color(X) with
p([t,f], ColorTable,[Gender,Cons]) }.
car_color(X, Color) :-
hair_color(City, HColor),
ccolor_table(X,CColorTable),
{ Color = ccolor(X) with
p([t,f], CColorTable,[HColor]) }.
height(X, Height) :-
gender(X, Gender),
height_table(X,HeightTable),
{ Height = height(X) with
p([t,f], HeightTable,[Gender]) }.
shoe_size(X, Shoesize) :-
height(X, Height),
shoe_size_table(X,ShoesizeTable),
{ Shoesize = shoe_size(X) with
p([t,f], ShoesizeTable,[Height]) }.
guilty(X, Guilt) :-
guilt_table(X, GuiltDist),
{ Guilt = guilt(X) with p([y,n], GuiltDist) }.
descn(X, Descn) :-
car_color(X, Car),
hair_color(X, Hair),
height(X, Height),
guilty(X, Guilt),
descn_table(X, DescTable),
{ Descn = descn(X) with
p([t,f], DescTable,[Car,Hair,Height,Guilt]) }.
witness(City, Witness) :-
descn(joe, DescnJ),
descn(1, Descn1),
wit_table(WitTable),
{ Witness = wit(City) with
p([t,f], WitTable,[DescnJ, Descn1]) }.

35
packages/CLPBN/examples/City/tables.yap
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cons_table(amsterdam,[0.2,
0.8]) :- !.
cons_table(_, [0.8,
0.2]).
color_table(_,
/* tm tf fm ff */
[ 0.05, 0.1, 0.3, 0.5 ,
0.95, 0.9, 0.7, 0.5 ]).
ccolor_table(_,
/* t f */
[ 0.9, 0.2 ,
0.1, 0.8 ]).
height_table(_,
/* m f */
[ 0.6, 0.4 ,
0.4, 0.6 ]).
shoe_size_table(_,
/* t f */
[ 0.9, 0.1 ,
0.1, 0.9 ]).
A: professor's ability;
B: student's grade (for course registration).
*/
descn_table(_,
/* color, hair, height, guilt */
/* ttttt tttf ttft ttff tfttt tftf tfft tfff ttttt fttf ftft ftff ffttt fftf ffft ffff */
/*t*/ [0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99,
/*f*/ 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01 ]).

47
packages/CLPBN/examples/burglary-alarm.fg Normal file
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5
1
0
2
2
0 0.001
1 0.999
1
1
2
2
0 0.002
1 0.998
3
1 0 2
2 2 2
8
0 0.95
1 0.94
2 0.29
3 0.001
4 0.05
5 0.06
6 0.71
7 0.999
2
2 3
2 2
4
0 0.9
1 0.05
2 0.1
3 0.95
2
2 4
2 2
4
0 0.7
1 0.01
2 0.3
3 0.99

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packages/CLPBN/examples/burglary-alarm.uai Normal file
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MARKOV
5
2 2 2 2 2
5
1 0
1 1
3 2 0 1
2 3 2
2 4 2
2
.001 .999
2
.002 .998
8
.95 .94 .29 .001
.05 .06 .71 .999
4
.9 .05
.1 .95
4
.7 .01
.3 .99

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packages/CLPBN/examples/burglary-alarm.yap Normal file
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:- use_module(library(pfl)).
%:- set_solver(fove).
%:- set_solver(hve).
%:- set_solver(bp).
%:- set_solver(cbp).
:- yap_flag(write_strings, off).
bayes burglary::[b1,b2] ; [0.001, 0.999] ; [].
bayes earthquake::[e1,e2] ; [0.002, 0.998]; [].
bayes alarm::[a1,a2], burglary, earthquake ;
[0.95, 0.94, 0.29, 0.001, 0.05, 0.06, 0.71, 0.999] ;
[].
bayes john_calls::[j1,j2], alarm ; [0.9, 0.05, 0.1, 0.95] ; [].
bayes mary_calls::[m1,m2], alarm ; [0.7, 0.01, 0.3, 0.99] ; [].
% ?- john_calls(J), mary_calls(m1).

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packages/CLPBN/examples/city.yap Normal file
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:- use_module(library(pfl)).
%:- set_solver(fove).
%:- set_solver(hve).
%:- set_solver(bp).
%:- set_solver(cbp).
:- multifile people/2.
:- multifile ev/1.
people(joe,nyc).
people(p2, nyc).
people(p3, nyc).
people(p4, nyc).
people(p5, nyc).
ev(descn(p2, t)).
ev(descn(p3, t)).
ev(descn(p4, t)).
ev(descn(p5, t)).
bayes city_conservativeness(C)::[y,n] ; cons_table(C) ; [people(_,C)].
bayes gender(P)::[m,f] ; gender_table(P) ; [people(P,_)].
bayes hair_color(P)::[t,f], city_conservativeness(C) ; hair_color_table(P) ; [people(P,C)].
bayes car_color(P)::[t,f], hair_color(P) ; car_color_table(P); [people(P,_)].
bayes height(P)::[t,f], gender(P) ; height_table(P) ; [people(P,_)].
bayes shoe_size(P):[t,f], height(P) ; shoe_size_table(P); [people(P,_)].
bayes guilty(P)::[y,n] ; guilty_table(P) ; [people(P,_)].
bayes descn(P)::[t,f], car_color(P), hair_color(P), height(P), guilty(P) ; descn_table(P) ; [people(P,_)].
bayes witness(C)::[t,f], descn(Joe), descn(P2) ; wit_table ; [people(_,C), Joe=joe, P2=p2].
% FIXME
%cons_table(amsterdam, [0.2, 0.8]) :- !.
cons_table(_, [0.8, 0.2]).
gender_table(_, [0.55, 0.45]).
hair_color_table(_,
/* conservative_city */
/* y n */
[ 0.05, 0.1,
0.95, 0.9 ]).
car_color_table(_,
/* t f */
[ 0.9, 0.2,
0.1, 0.8 ]).
height_table(_,
/* m f */
[ 0.6, 0.4,
0.4, 0.6 ]).
shoe_size_table(_,
/* t f */
[ 0.9, 0.1,
0.1, 0.9 ]).
guilty_table(_, [0.23, 0.77]).
descn_table(_,
/* color, hair, height, guilt */
/* ttttt tttf ttft ttff tfttt tftf tfft tfff ttttt fttf ftft ftff ffttt fftf ffft ffff */
[ 0.99, 0.5, 0.23, 0.88, 0.41, 0.3, 0.76, 0.87, 0.44, 0.43, 0.29, 0.72, 0.23, 0.91, 0.95, 0.92,
0.01, 0.5, 0.77, 0.12, 0.59, 0.7, 0.24, 0.13, 0.56, 0.57, 0.71, 0.28, 0.77, 0.09, 0.05, 0.08]).
wit_table([0.2, 0.45, 0.24, 0.34,
0.8, 0.55, 0.76, 0.66]).
runall(G, Wrapper) :-
findall(G, Wrapper, L),
execute_all(L).
execute_all([]).
execute_all(G.L) :-
call(G),
execute_all(L).
is_joe_guilty(Guilty) :-
witness(nyc, t),
runall(X, ev(X)),
guilty(joe, Guilty).
% ?- is_joe_guilty(Guilty)

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packages/CLPBN/examples/comp_workshops.yap Normal file
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:- use_module(library(pfl)).
%:- set_solver(fove).
%:- set_solver(hve).
%:- set_solver(bp).
%:- set_solver(cbp).
:- yap_flag(write_strings, off).
:- multifile c/2.
c(p1,w1).
c(p1,w2).
c(p1,w3).
c(p2,w1).
c(p2,w2).
c(p2,w3).
c(p3,w1).
c(p3,w2).
c(p3,w3).
c(p4,w1).
c(p4,w2).
c(p4,w3).
c(p5,w1).
c(p5,w2).
c(p5,w3).
markov attends(P)::[t,f], hot(W)::[t,f] ; [0.2, 0.8, 0.8, 0.8] ; [c(P,W)].
markov attends(P)::[t,f], series::[t,f] ; [0.501, 0.499, 0.499, 0.499] ; [c(P,_)].
% ?- series(X).

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packages/CLPBN/examples/fail1.yap Normal file
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:- use_module(library(pfl)).
:- set_pfl_flag(solver,fove).
%:- set_pfl_flag(solver,bp), clpbn_horus:set_horus_flag(inf_alg,ve).
%:- set_pfl_flag(solver,bp), clpbn_horus:set_horus_flag(inf_alg,bp).
%:- set_pfl_flag(solver,bp), clpbn_horus:set_horus_flag(inf_alg,cbp).
t(ann).
t(dave).
% p(ann,t).
markov p(X)::[t,f] ; [0.1, 0.3] ; [t(X)].
% use standard Prolog queries: provide evidence first.
?- p(ann,t), p(ann,X).
% ?- p(ann,X).

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packages/CLPBN/examples/fail2.yap Normal file
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:- use_module(library(pfl)).
:- set_solver(fove).
%:- set_solver(hve).
%:- set_solver(bp).
%:- set_solver(cbp).
:- yap_flag(write_strings, off).
:- clpbn_horus:set_horus_flag(verbosity,5).
people(p1,p1).
people(p1,p2).
people(p2,p1).
people(p2,p2).
markov p(A,A)::[t,f] ; [1.0,4.5] ; [people(A,_)].
markov p(A,B)::[t,f] ; [1.0,4.5] ; [people(A,B)].
?- p(p1,p1,X).

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packages/CLPBN/examples/social_domain1.yap Normal file
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:- use_module(library(pfl)).
%:- set_solver(fove).
%:- set_solver(hve).
%:- set_solver(bp).
%:- set_solver(cbp).
:- yap_flag(write_strings, off).
:- multifile people/1.
people @ 5.
people(X,Y) :-
people(X),
people(Y),
X \== Y.
markov smokes(X)::[t,f]; [1.0, 4.0552]; [people(X)].
markov cancer(X)::[t,f]; [1.0, 9.9742]; [people(X)].
markov friends(X,Y)::[t,f] ; [1.0, 99.48432] ; [people(X,Y)].
markov smokes(X)::[t,f], cancer(X)::[t,f] ; [4.48169, 4.48169, 1.0, 4.48169] ; [people(X)].
markov friends(X,Y)::[t,f], smokes(X)::[t,f], smokes(Y)::[t,f] ;
[3.004166, 3.004166, 3.004166, 3.004166, 3.004166, 1.0, 1.0, 3.004166] ; [people(X,Y)].
% ?- friends(p1,p2,X).

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packages/CLPBN/examples/social_domain2.yap Normal file
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:- use_module(library(pfl)).
%:- set_solver(fove).
%:- set_solver(hve).
%:- set_solver(bp).
%:- set_solver(cbp).
:- yap_flag(write_strings, off).
:- multifile people/1.
people @ 5.
people(X,Y) :-
people(X),
people(Y).
% X \== Y.
markov smokes(X)::[t,f]; [1.0, 4.0552]; [people(X)].
markov asthma(X)::[t,f]; [1.0, 9.9742] ; [people(X)].
markov friends(X,Y)::[t,f]; [1.0, 99.48432] ; [people(X,Y)].
markov asthma(X)::[t,f], smokes(X)::[t,f]; [4.48169, 4.48169, 1.0, 4.48169] ; [people(X)].
markov asthma(X)::[t,f], friends(X,Y)::[t,f], smokes(Y)::[t,f];
[3.004166, 3.004166, 3.004166, 3.004166, 3.004166, 1.0, 1.0, 3.004166] ; [people(X,Y)].
% ?- smokes(p1,t), smokes(p2,t), friends(p1,p2,X)

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packages/CLPBN/examples/workshop_attrs.yap Normal file
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:- use_module(library(pfl)).
%:- set_solver(fove).
%:- set_solver(hve).
%:- set_solver(bp).
%:- set_solver(cbp).
:- yap_flag(write_strings, off).
:- multifile people/1.
people @ 5.
markov attends(P)::[t,f], attr1::[t,f] ; [0.7, 0.3, 0.3, 0.3] ; [people(P)].
markov attends(P)::[t,f], attr2::[t,f] ; [0.7, 0.3, 0.3, 0.3] ; [people(P)].
markov attends(P)::[t,f], attr3::[t,f] ; [0.7, 0.3, 0.3, 0.3] ; [people(P)].
markov attends(P)::[t,f], attr4::[t,f] ; [0.7, 0.3, 0.3, 0.3] ; [people(P)].
markov attends(P)::[t,f], attr5::[t,f] ; [0.7, 0.3, 0.3, 0.3] ; [people(P)].
markov attends(P)::[t,f], attr6::[t,f] ; [0.7, 0.3, 0.3, 0.3] ; [people(P)].
markov attends(P)::[t,f], series::[t,f] ; [0.501, 0.499, 0.499, 0.499] ; [people(P)].
% ?- series(X).