Algorithm-SAT-Backtracking
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? 0
: 1
} @{$clauses}
) == 0
);
#If any variable is true, then the clause is true.
return 1
if (
( grep {
( defined $self->resolve( $_, $model )
and $self->resolve( $_, $model ) == 1 )
? 1
: 0
} @{$clauses}
) > 0
);
# Otherwise, we don't know what the clause is.
return undef;
}
1;
__END__
=encoding utf-8
=head1 NAME
Algorithm::SAT::Backtracking - A simple Backtracking SAT solver written in pure Perl
=head1 SYNOPSIS
# You can use it with Algorithm::SAT::Expression
use Algorithm::SAT::Expression;
my $expr = Algorithm::SAT::Expression->new->with("Algorithm::SAT::Backtracking"); #Uses Algorithm::SAT::Backtracking by default, so with() it's not necessary in this case
$expr->or( '-foo@2.1', 'bar@2.2' );
$expr->or( '-foo@2.3', 'bar@2.2' );
$expr->or( '-baz@2.3', 'bar@2.3' );
$expr->or( '-baz@1.2', 'bar@2.2' );
my $model = $exp->solve();
# Or you can use it directly:
use Algorithm::SAT::Backtracking;
my $solver = Algorithm::SAT::Backtracking->new;
my $variables = [ 'blue', 'green', 'yellow', 'pink', 'purple' ];
my $clauses = [
[ 'blue', 'green', '-yellow' ],
[ '-blue', '-green', 'yellow' ],
[ 'pink', 'purple', 'green', 'blue', '-yellow' ]
];
my $model = $solver->solve( $variables, $clauses );
=head1 DESCRIPTION
Algorithm::SAT::Backtracking is a pure Perl implementation of a simple SAT Backtracking solver.
In computer science, the Boolean Satisfiability Problem (sometimes called Propositional Satisfiability Problem and abbreviated as I<SATISFIABILITY> or I<SAT>) is the problem of determining if there exists an interpretation that satisfies a given Bool...
For example, the formula "a AND NOT b" is satisfiable because one can find the values a = B<TRUE> and b = B<FALSE>, which make (a AND NOT b) = TRUE. In contrast, "a AND NOT a" is unsatisfiable. More: L<https://en.wikipedia.org/wiki/Boolean_satisfiabi...
Have a look also at the tests file for an example of usage.
L<Algorithm::SAT::Expression> use this module to solve Boolean expressions.
=head1 METHODS
=head2 solve()
The input consists of a boolean expression in Conjunctive Normal Form.
This means it looks something like this:
`(blue OR green) AND (green OR NOT yellow)`
We encode this as an array of strings with a `-` in front for negation:
`[['blue', 'green'], ['green', '-yellow']]`
Hence, each row means an B<AND>, while a list groups two or more B<OR> clauses.
Returns 0 if the expression can't be solved with the given clauses, the model otherwise in form of a hash .
Have a look at L<Algorithm::SAT::Expression> to see how to use it in a less painful way.
=head2 resolve()
Uses the model to resolve some variable to its actual value, or undefined if not present.
my $model = { blue => 1, red => 0 };
my $a=$solver->resolve( "blue", $model );
#$a = 1
=head2 satisfiable()
Determines whether a clause is satisfiable given a certain model.
my $model
= { pink => 1, purple => 0, green => 0, yellow => 1, red => 0 };
my $a=$solver->satisfiable( [ 'purple', '-pink' ], $model );
#$a = 0
=head2 update()
Copies the model, then sets `choice` = `value` in the model, and returns it.
my $model
= { pink => 1, red => 0, purple => 0, green => 0, yellow => 1 };
my $new_model = $solver->update( $model, 'foobar', 1 );
# now $new_model->{foobar} is 1
=head1 LICENSE
Copyright (C) mudler.
This library is free software; you can redistribute it and/or modify
it under the same terms as Perl itself.
=head1 AUTHOR
mudler E<lt>mudler@dark-lab.netE<gt>
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