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lib/AI/Logic/AnswerSet.pm  view on Meta::CPAN

	}
	elsif($operator eq "<=") {
		if($value <= $num) {
			return 1;
		}
		return 0;
	}
	return 0;
}

sub mapAS {	#Mapping of the Answer Sets in an array of hashes

	my $countAS = 0;

	my @answerSets = @{$_[0]};

	my @second;
	if($_[1]) {
		@second = @{$_[1]};
	}

lib/AI/Logic/AnswerSet.pm  view on Meta::CPAN

=head1 SYNOPSIS

  use AI::Logic::AnswerSet;
  
  # invoke DLV( AnwerSetProgramming-based system) and save the stdoutput
  my @stdoutput = AI::Logic::AnswerSet::singleExec("3-colorability.txt");

  # parse the output
  my @res = AI::Logic::AnswerSet::getAS(@stdoutput);

  # map the results
  my @mappedAS = AI::Logic::AnswerSet::mapAS(\@res);

  # get a predicate from the results
  my @col = AI::Logic::AnswerSet::getPred(\@mappedAS,1,"col");

  # get a term of a predicate
  my @term = AI::Logic::AnswerSet::getProjection(\@mappedAS,1,"col",2);


=head1 DESCRIPTION

This extension allows to interact with DLV, an Artificial Intelligence system
for Answer Set Programming (ASP).
Please note that the DLV system must appear in the same folder of the perl program
and it must be renamed as "dlv";
DLV can be freely obtained at www.dlvsystem.com.
For further info about DLV and Answer Set Programming please start from www.dlvsystem.com.

lib/AI/Logic/AnswerSet.pm  view on Meta::CPAN

	AI::Logic::AnswerSet::executeFromFileAndSave("outprog.txt","dlvprog.txt","");
	my @result = AI::Logic::AnswerSet::getASFromFile("outprog.txt");

=head3 getAS

Parses the output of a DLV execution and gather the answer sets.

	my @out = AI::Logic::AnswerSet::singleExec("3col.txt","nodes.txt","edges.txt","-nofacts");
	my @result = AI::Logic::AnswerSet::getAS(@out);

=head3 mapAS

Parses the new output in order to save and organize the results into a hashmap.

	my @out = AI::Logic::AnswerSet::singleExec("3col.txt","nodes.txt","edges.txt","-nofacts");
	my @result = AI::Logic::AnswerSet::getAS(@out);
	my @mappedAS = AI::Logic::AnswerSet::mapAS(@result);

The user can set some constraints on the data to be saved in the hashmap, such as predicates, or answer sets, or both.

	my @mappedAS = AI::Logic::AnswerSet::mapAS(@result,@predicates,@answerSets);

For instance, think about the 3-colorability problem: imagine to 
have the edges in the hashmap, and to print the edges contained in the third answer set
returned by DLV; this is an example of the print instruction, useful to understand how
the hashmap works:

	print "Edges: @{$mappedAS[2]{edge}}\n";

In this case, we are printing the array containing the predicate "edge".

=head3 getPred

Easily manage the hashmap and get the desired predicate(see the print example
described in the method above):

	my @edges = AI::Logic::AnswerSet::getPred(\@mappedAS,3,"edge");

=head3 getProjection

Returns the projection of the n-th term of a specified predicate.
Suppose that we have the predicate "person" C<person(Name,Surename);> and
that we just want the surenames of all the instances of "person":

	my @surenames = AI::Logic::AnswerSet::getProjection(\@mappedAS,3,"person",2);

The parameters are, respectively: hashmap, number of the answer set, name of the predicate,
position of the term.

=head3 statistics

This method returns an array of hashes with some stats of every predicate of every answer set,
namely the number of occurrences of the specified predicates of each answer set.
If a condition is specified(number of predicates), only the answer sets that satisfy
the condition are returned.

	my @res = AI::Logic::AnswerSet::getAS(@output);
	my @predicates = ("node","edge");
	my @stats = AI::Logic::AnswerSet::statistics(\@res,\@predicates);

In this case the data structure returned is the same as the one returned by C<mapAS()>.
Hence, for each answer set (each element of the array of hashes), the hashmap will appear 
like this:

	{
		node => 6
		edge => 9
	}

This means that for a particular answer set we have 6 nodes and 9 edges.
In addition, this method can be used with some constraints: