/* 

  Inductive Logic Programming in Picat v3.

  This is a port of the program minihyper.pl + examples in
  I. Bratko, "Prolog Programming for Artificial Intelligence", 4th edn.,
  Pearson Education / Addison-Wesley 2012
  Page 495ff (Figure 21.4)
       
  The module minihyper_v3 is defined in
  See http://hakank.org/picat/minihyper_v3.pi 

  Output:
"""
MaxD = 0
MaxD = 1
MaxD = 2
MaxD = 3
MaxD = 4
[[has_daughter(_a58),parent(_a58,_ae8),female(_ae8)] / [_a58,_ae8]]
"""

  [[has_daughter(A),parent(A,B),female(B)] / [A,B]]

  This Picat model was created by Hakan Kjellerstrand, hakank@gmail.com
  See also my Picat page: http://www.hakank.org/picat/

*/

import minihyper_v3.

main => go.


go ?=>
  induce(H),
  println(H),
  fail,
  
  nl.

go => true.


% Default parameter settings

max_proof_length( 6).   % Max. proof length, counting calls to 'non-prolog' pred.

max_clause_length( 3).  % Max. number of literals in a clause


% hakank: This is the input data for the problem
% Fig 21.1
% Figure 21.1  A definition of the problem of learning predicate has_daughter.

% Learning from family relations

% Background knowledge

backliteral( parent(X,Y),  [X,Y]).  % A background literal with vars. [X,Y]
backliteral( male(X), [X]).
backliteral( female(X), [X]).

prolog_predicate( parent(_,_)).     % Goal parent(_,_) executed directly by Prolog
prolog_predicate( male(_)).
prolog_predicate( female(_)).

parent( pam, bob).
parent( tom, bob).
parent( tom, liz).
parent( bob, ann).
parent( bob, pat).
parent( pat, jim).
parent( pat, eve).

female( pam).
female( liz).
female( ann).
female( pat).
female( eve).

male( tom).
male( bob).
male( jim).


% Positive examples

ex( has_daughter(tom)).       % Tom has a daughter
ex( has_daughter(bob)).
ex( has_daughter(pat)).

% Negative examples

nex( has_daughter(pam)).      % Pam doen't have a daughter
nex( has_daughter(jim)).

start_hyp( [ [has_daughter(X)] / [X] ] ).      % Starting hypothesis


% hakank: Another a little more complex example from page 500 with