AI-Logic-AnswerSet
view release on metacpan or search on metacpan
metafile : create_distdir
$(NOECHO) $(ECHO) Generating META.yml
$(NOECHO) $(ECHO) '--- #YAML:1.0' > META_new.yml
$(NOECHO) $(ECHO) 'name: AI-Logic-AnswerSet' >> META_new.yml
$(NOECHO) $(ECHO) 'version: 0.01' >> META_new.yml
$(NOECHO) $(ECHO) 'abstract: Perl extension for embedding ASP (Answer Set Programming) programs in Perl.' >> META_new.yml
$(NOECHO) $(ECHO) 'author:' >> META_new.yml
$(NOECHO) $(ECHO) ' - leviathan <leviathan@>' >> META_new.yml
$(NOECHO) $(ECHO) 'license: unknown' >> META_new.yml
$(NOECHO) $(ECHO) 'distribution_type: module' >> META_new.yml
$(NOECHO) $(ECHO) 'configure_requires:' >> META_new.yml
$(NOECHO) $(ECHO) ' ExtUtils::MakeMaker: 0' >> META_new.yml
$(NOECHO) $(ECHO) 'build_requires:' >> META_new.yml
$(NOECHO) $(ECHO) ' ExtUtils::MakeMaker: 0' >> META_new.yml
$(NOECHO) $(ECHO) 'requires: {}' >> META_new.yml
$(NOECHO) $(ECHO) 'no_index:' >> META_new.yml
$(NOECHO) $(ECHO) ' directory:' >> META_new.yml
$(NOECHO) $(ECHO) ' - t' >> META_new.yml
$(NOECHO) $(ECHO) ' - inc' >> META_new.yml
$(NOECHO) $(ECHO) 'generated_by: ExtUtils::MakeMaker version 6.55_02' >> META_new.yml
$(NOECHO) $(ECHO) 'meta-spec:' >> META_new.yml
$(NOECHO) $(ECHO) ' url: http://module-build.sourceforge.net/META-spec-v1.4.html' >> META_new.yml
$(NOECHO) $(ECHO) ' version: 1.4' >> META_new.yml
-$(NOECHO) $(MV) META_new.yml $(DISTVNAME)/META.yml
$(NOECHO) $(NOOP)
# --- MakeMaker perldepend section:
# --- MakeMaker makefile section:
# We take a very conservative approach here, but it's worth it.
# We move Makefile to Makefile.old here to avoid gnu make looping.
$(FIRST_MAKEFILE) : Makefile.PL $(CONFIGDEP)
$(NOECHO) $(ECHO) "Makefile out-of-date with respect to $?"
$(NOECHO) $(ECHO) "Cleaning current config before rebuilding Makefile..."
-$(NOECHO) $(RM_F) $(MAKEFILE_OLD)
-$(NOECHO) $(MV) $(FIRST_MAKEFILE) $(MAKEFILE_OLD)
- $(MAKE) $(USEMAKEFILE) $(MAKEFILE_OLD) clean $(DEV_NULL)
$(PERLRUN) Makefile.PL
$(NOECHO) $(ECHO) "==> Your Makefile has been rebuilt. <=="
$(NOECHO) $(ECHO) "==> Please rerun the $(MAKE) command. <=="
$(FALSE)
AI-Logic-AnswerSet version 0.01
===============================
Answer Set Programming (ASP) is a very powerful formalism tool for knowledge representation and reasoning,
which is lately getting quite popular, also thanks to the availability of a number of modern
and solid systems supporting it, such as DLV.
The main goal of this module is to “embed†DLV into Perl programs in such a way that a programmer
can easily ask DLV for some jobs and then easily exploit its output.
So, how does it work? The user can write down (or compose!) his/her declarative solutions;
AI::Logic::AnswerSet takes care of interacting with DLV and makes results available into Perl,
where they can be easily managed by the user.
NOTE: the use of this framework requires at least some basics of declarative programming, ASP in particular;
in addition, the DLV system is needed.
The user might refer to www.dlvsystem.com for downloading DLV and getting some info on its language.
INSTALLATION
To install this module type the following:
perl Makefile.PL
make
make test
make install
DEPENDENCIES
This module requires no other modules and libraries
COPYRIGHT AND LICENCE
Copyright (C) 2012 by Ferdinando Primerano, Francesco Calimeri.
This work started within the bachelor degree thesis program of the
Computer Science course at Department of Mathematics of the University
of Calabria.
This library is free software; you can redistribute it and/or modify
lib/AI/Logic/AnswerSet.pm view on Meta::CPAN
close DLVW;
open(SAVESTDOUT, ">&STDOUT") or die "Can't save STDOUT: $!\n";
open(STDOUT, ">$_[0]") or die "Can't open STDOUT to $_[0]", "$!\n";
my @args = ("./dlv", "$_[1]");
system(@args) == 0
or die "system @args failed: $?";
open(STDOUT,">&SAVESTDOUT"); #close file and restore STDOUT
close OUTPUT;
}
sub executeAndSave { #Executes DLV and saves the output of the program written by the user in a file
open(SAVESTDOUT, ">&STDOUT") or die "Can't save STDOUT: $!\n";
open(STDOUT, ">$_[0]") or die "Can't open STDOUT to $_[0]", "$!\n";
my @args = ("./dlv --");
system(@args) == 0 or die "system @args failed: $?";
open(STDOUT,">&SAVESTDOUT"); #close file and restore STDOUT
close OUTPUT;
}
sub iterativeExec { # Executes an input program with several instances and stores them in a bidimensional array
my @input = @_;
my @returned_value;
if(@input) {
my $option = $input[$#input];
if($option =~ /^-/) {
lib/AI/Logic/AnswerSet.pm view on Meta::CPAN
}
else {
print "INPUT ERROR\n";
}
return @returned_value;
}
sub singleExec { # Executes a single input program or opens the DLV terminal and stores it in an array
my @input = @_;
my @returned_value;
if(@input) {
my @args = ("./dlv", "@input");
(@returned_value) = `@args`;
lib/AI/Logic/AnswerSet.pm view on Meta::CPAN
else {
$program = \($_[0]);
$$program = "$$program $code";
}
}
sub getASFromFile { #Gets the Answer Set from the file where the output was saved
open RESULT, "<", "$_[0]" or die $!;
my @result = <RESULT>;
my @arr;
foreach my $line (@result) {
if($line =~ /\{\w*/) {
$line =~ s/(\{|\})//g;
#$line =~ s/\n//g; # delete \n from $line
my @tmp = split(', ', $line);
push @arr, @tmp;
}
}
close RESULT;
return @arr;
}
sub getAS { #Returns the Answer Sets from the array where the output was saved
my @result = @_;
my @arr;
foreach my $line (@result) {
if($line =~ /\{\w*/) {
$line =~ s/(\{|\})//g;
$line =~ s/(Best model:)//g;
my @tmp = split(', ', $line);
push @arr, @tmp;
}
}
lib/AI/Logic/AnswerSet.pm view on Meta::CPAN
my @pr = @{$_[0]};
return @{$pr[$_[1]]{$_[2]}};
}
sub getProjection { #Returns the values selected by the user
my @pr = @{$_[0]};
my @projection;
my @res = @{$pr[$_[1]]{$_[2]}};
my $size = @res;
my $fieldsStr;
for(my $i = 0; $i < $size; $i++) {
my $pred = @{$pr[$_[1]]{$_[2]}}[$i];
if($pred =~ /(\w+)\((.+)\)/) {
$fieldsStr = $2;
}
my @fields = split(',',$fieldsStr);
push @projection , $fields[$_[3]-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.
The module was originally published as "ASPerl", but suffered from
some problems with the namespace, now changed. The module has been
also significantly rearranged according to the advices coming from the
community. Thank you all!
If you are using this module, please let us know: we are always
interested in end-users desires, and we wish to improve our library:
comments are truly welcome!
=head2 Methods
=head3 executeFromFileAndSave
This method allows to execute DLV with and input file and save the output in another file.
AI::Logic::AnswerSet::executeFromFileAndSave("outprog.txt","dlvprog.txt","");
In this case the file "outprog.txt" consists of the result of the DLV invocation
with the file "dlvprog.txt".
No code is specified in the third value of the method. It can be used to add code
to an existing file or to a new one.
AI::Logic::AnswerSet::executeFromFileAndSave("outprog.txt","dlvprog.txt",
"b(X):-a(X). a(1).");
=head3 executeAndSave
To call DLV without an input file, directly writing the ASP code from the terminal,
use this method, passing only the name of the output file.
AI::Logic::AnswerSet::executeAndSave("outprog.txt");
Press Ctrl+D to stop using the DLV terminal and execute the program.
=head3 singleExec
Use this method to execute DLV whit several input files, including also
DLV options like "-nofacts".
The output will be stored inside an array.
my @out = AI::Logic::AnswerSet::singleExec("3col.txt","nodes.txt","edges.txt","-nofacts");
Another way to use this method:
my @out = AI::Logic::AnswerSet::singleExec();
In this way it will work like C<executeAndSave()> without saving the output to a file.
=head3 iterativeExec
This method allows to call multiples DLV executions for several instances of the same problem.
Suppose you have a program that calculates the 3-colorability of a graph; in this case
one might have more than a graph, and each graph instance can be stored in a different file.
A Perl programmer might want to work with the results of all the graphs she has in her files,
so this function will be useful for this purpose.
Use it like in the following:
my @outputs = AI::Logic::AnswerSet::iterativeExec("3col.txt","nodes.txt","./instances");
In this case the nodes of each graph are the same, but not the edges.
Notice that in order to correctly use this method, the user must specify the path
to the instances (the edges, in this case).
The output of this function is a two-dimensional array; each element corresponds to the result
of a single DLV execution, exactly as in the case of the function C<singleExec()>.
=head3 selectOutput
This method allows to get one of the results of C<iterativeExec>.
my @outputs = AI::Logic::AnswerSet::iterativeExec("3col.txt","nodes.txt","./instances");
my @out = AI::Logic::AnswerSet::selectOutput(\@outputs,0);
In this case the first output is selected.
=head3 getASFromFile
Parses the output of a DLV execution saved in a file and gather the answer sets.
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".
lib/AI/Logic/AnswerSet.pm view on Meta::CPAN
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:
my @res = AI::Logic::AnswerSet::getAS(@output);
my @predicates = ("node,"edge");
my @numbers = (4,15);
my @operators = (">","<");
my @stats = AI::Logic::AnswerSet::statistics(\@res,\@predicates,\@numbers,\@operators);
Now the functions returns the answer sets that satisfy the condition, i.e., an answer set
is returned only if the number of occurrences of the predicate "node" is higher than 4, and the number of occurrences of the predicate "edge" less than 15.
=head3 getFacts
Get the logic program facts from a file or a string.
my @facts = AI::Logic::AnswerSet::getFacts($inputFile);
lib/AI/Logic/AnswerSet.pm view on Meta::CPAN
AI::Logic::AnswerSet::addCode($file,"b(3). b(4).");
=head3 createNewFile
Creates a new file with some code.
AI::Logic::AnswerSet::createNewFile($file,"b(3). b(4).");
=head3 addFacts
Quiclky adds facts to a file. Imagine to have some data(representing facts)
stored inside an array; just use this method to put them in a file and give it a name.
AI::Logic::AnswerSet::addFacts("villagers",\@villagers,">","villagersFile.txt");
In the example above, "villagers" will be the name of the facts; C<@villagers> is the array
containing the data; ">" is the file operator(will create a new file, in this case);
"villagersFile.txt" is the filename. The file will contain facts of the form "villagers(X)",
for each "X", appearing in the array C<@villagers>.
( run in 0.906 second using v1.01-cache-2.11-cpan-49f99fa48dc )