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    my $vals = $self->_cat_array_of_piddles(@vals);
    return $vals->mv(-1, 0)->maximum;
}

sub not {
    my ($self, $val) = @_;
    return 1-$val;
}

sub true  { return 1 }

sub false { return 0 }

sub new_variable {
    my ($self, @pars) = @_;

    my $variable_class = $self->_class_of_variable();
    my $var = $variable_class->new($self, @pars);
    push @{$self->{_variables}}, $var;
    Scalar::Util::weaken $self->{_variables}->[-1];
    return $var;
}

sub reset {
    my ($self) = @_;
    $_->reset() for $self->variables(); 
    return $self;
}

sub _class_of_variable { 'AI::FuzzyEngine::Variable' }

sub _non_is_a_piddle {
    return List::MoreUtils::none {ref $_ eq 'PDL'} @_;
}

my $_PDL_is_imported;
sub _check_for_PDL {
    return if $_PDL_is_imported;
    die "PDL not loaded"       unless $INC{'PDL.pm'};
    die "PDL::Core not loaded" unless $INC{'PDL/Core.pm'};
    $_PDL_is_imported = 1;
}

sub _cat_array_of_piddles {
    my ($class, @vals)  = @_;

    # TODO: Rapid return if @_ == 1 (isa piddle)
    # TODO: join "-", ndims -> Schnellcheck auf gleiche Dim.

    # All elements must get piddles
    my @pdls  = map { PDL::Core::topdl($_) } @vals;

    # Get size of wrapping piddle (using a trick)
    # applying valid expansion rules for element wise operations
    my $zeros = PDL->pdl(0);
    #        v-- does not work due to threading mechanisms :-((
    # $zeros += $_ for @pdls;
    # Avoid threading!
    for my $p (@pdls) {
        croak "Empty piddles are not allowed" if $p->isempty();
        eval { $zeros = $zeros + $p->zeros(); 1
            } or croak q{Can't expand piddles to same size};
    }

    # Now, cat 'em by expanding them on the fly
    my $vals = PDL::cat( map {$_ + $zeros} @pdls );
    return $vals;
};

1;

=pod

=head1 NAME

AI::FuzzyEngine - A Fuzzy Engine, PDL aware

=head1 SYNOPSIS

=head2 Regular Perl - without PDL

    use AI::FuzzyEngine;

    # Engine (or factory) provides fuzzy logical arithmetic
    my $fe = AI::FuzzyEngine->new();

    # Disjunction:
    my $a = $fe->or ( 0.2, 0.5, 0.8, 0.7 ); # 0.8
    # Conjunction:
    my $b = $fe->and( 0.2, 0.5, 0.8, 0.7 ); # 0.2
    # Negation:
    my $c = $fe->not( 0.4 );                # 0.6
    # Always true:
    my $t = $fe->true();                    # 1.0
    # Always false:
    my $f = $fe->false();                   # 0.0

    # These functions are constitutive for the operations
    # on the fuzzy sets of the fuzzy variables:

    # VARIABLES (AI::FuzzyEngine::Variable)

    # input variables need definition of membership functions of their sets
    my $flow = $fe->new_variable( 0 => 2000,
                        small => [0, 1,  500, 1, 1000, 0                  ],
                        med   => [       400, 0, 1000, 1, 1500, 0         ],
                        huge  => [               1000, 0, 1500, 1, 2000, 1],
                   );
    my $cap  = $fe->new_variable( 0 => 1800,
                        avg   => [0, 1, 1500, 1, 1700, 0         ],
                        high  => [      1500, 0, 1700, 1, 1800, 1],
                   );
    # internal variables need sets, but no membership functions
    my $saturation = $fe->new_variable( # from => to may be ommitted
                        low   => [],
                        crit  => [],
                        over  => [],
                   );
    # But output variables need membership functions for their sets:
    my $green = $fe->new_variable( -5 => 5,
                        decrease => [-5, 1, -2, 1, 0, 0            ],