File Coverage

blib/lib/Game/Theory/TwoPersonMatrix.pm

Criterion	Covered	Total	%
statement	244	244	100.0
branch	45	48	93.7
condition	24	33	72.7
subroutine	26	26	100.0
pod	12	12	100.0
total	351	363	96.6

package Game::Theory::TwoPersonMatrix;
our $AUTHORITY = 'cpan:GENE';

# ABSTRACT: Analyze a 2 person matrix game

use strict;
use warnings;

our $VERSION = '0.2206';

use Carp;
use Algorithm::Combinatorics qw( permutations );
use Array::Transpose;
use List::SomeUtils qw( all zip );
use List::Util qw( max min sum0 );
use List::Util::WeightedChoice qw( choose_weighted );



sub new {
    my $class = shift;
    my %args = @_;
    my $self = {
        1 => $args{1},
        2 => $args{2},
        payoff => $args{payoff},
        payoff1 => $args{payoff1},
        payoff2 => $args{payoff2},
    };
    bless $self, $class;
    return $self;
}


sub expected_payoff
{
    my ($self) = @_;

    my $expected_payoff;

    # For each strategy of player 1...
    for my $i ( sort keys %{ $self->{1} } )
    {
        # For each strategy of player 2...
        for my $j ( sort keys %{ $self->{2} } )
        {
            # Expected value is the sum of the probabilities of each payoff
            if ( $self->{payoff1} && $self->{payoff2} )
            {
                $expected_payoff->[0] += $self->{1}{$i} * $self->{2}{$j} * $self->{payoff1}[$i - 1][$j - 1];
                $expected_payoff->[1] += $self->{1}{$i} * $self->{2}{$j} * $self->{payoff2}[$i - 1][$j - 1];
            }
            else {
                $expected_payoff += $self->{1}{$i} * $self->{2}{$j} * $self->{payoff}[$i - 1][$j - 1];
            }
        }
    }

    return $expected_payoff;
}


sub s_expected_payoff
{
    my ($self) = @_;

    my $expected_payoff;

    # For each strategy of player 1...
    for my $i ( sort keys %{ $self->{1} } )
    {
        # For each strategy of player 2...
        for my $j ( sort keys %{ $self->{2} } )
        {
            # Expected value is the sum of the probabilities of each payoff
            if ( $self->{payoff1} && $self->{payoff2} )
            {
                $expected_payoff->[0] .= " + $self->{1}{$i} * $self->{2}{$j} * $self->{payoff1}[$i - 1][$j - 1]";
                $expected_payoff->[1] .= " + $self->{1}{$i} * $self->{2}{$j} * $self->{payoff2}[$i - 1][$j - 1]";
            }
            else {
                $expected_payoff .= " + $self->{1}{$i} * $self->{2}{$j} * $self->{payoff}[$i - 1][$j - 1]";
            }
        }
    }

    my $deplus = sub
    {
        my ($string) = @_;
        $string =~ s/^ \+ (.+)$/$1/;
        return $string;
    };

    if ( $self->{payoff1} && $self->{payoff2} )
    {
        $expected_payoff->[0] = $deplus->($expected_payoff->[0]);
        $expected_payoff->[1] = $deplus->($expected_payoff->[1]);
    }
    else {
        $expected_payoff = $deplus->($expected_payoff);
    }

    return $expected_payoff;
}


sub counter_strategy
{
    my ( $self, $player ) = @_;

    my $counter_strategy = [];
    my %seen;

    my $opponent = $player == 1 ? 2 : 1;

    my @keys = 1 .. keys %{ $self->{$player} };
    my @pure = ( 1, (0) x ( @keys - 1 ) );

    my $i = permutations( \@pure );

    while ( my $strategies = $i->next )
    {
        next if $seen{"@$strategies"}++;

        my $g = Game::Theory::TwoPersonMatrix->new(
            $player   => { zip @keys, @$strategies },
            $opponent => $self->{$opponent},
            payoff    => $self->{payoff} || $self->{"payoff$player"},
        );

        push @$counter_strategy, $g->expected_payoff;
    }

    return $counter_strategy;
}


sub saddlepoint
{
    my ($self) = @_;

    my $saddlepoint;

    my $rsize = @{ $self->{payoff} } - 1;
    my $csize = @{ $self->{payoff}[0] } - 1;

    for my $row ( 0 .. $rsize )
    {
        # Get the minimum value of the current row
        my $min = min @{ $self->{payoff}[$row] };

        # Inspect each column given the row
        for my $col ( 0 .. $csize )
        {
            # Get the payoff
            my $val = $self->{payoff}[$row][$col];

            # Is the payoff also the row minimum?
            if ( $val == $min )
            {
                # Gather the column values for each row
                my @col;
                for my $r ( 0 .. $rsize )
                {
                    push @col, $self->{payoff}[$r][$col];
                }
                # Get the maximum value of the columns
                my $max = max @col;

                # Is the payoff also the column maximum?
                if ( $val == $max )
                {
                    $saddlepoint->{"$row,$col"} = $val;
                }
            }
        }
    }

    return $saddlepoint;
}


sub oddments
{
    my ($self) = @_;

    my $rsize = @{ $self->{payoff}[0] };
    my $csize = @{ $self->{payoff} };
    carp 'Payoff matrix must be 2x2' unless $rsize == 2 && $csize == 2;

    my ( $player, $opponent );

    my $A = $self->{payoff}[0][0];
    my $B = $self->{payoff}[0][1];
    my $C = $self->{payoff}[1][0];
    my $D = $self->{payoff}[1][1];

    my ( $x, $y );
    $x = abs( $D - $C );
    $y = abs( $A - $B );
    my $i = $x / ( $x + $y );
    my $j = $y / ( $x + $y );
    $player = [ $i, $j ];

    $x = abs( $D - $B );
    $y = abs( $A - $C );
    $i = $x / ( $x + $y );
    $j = $y / ( $x + $y );
    $opponent = [ $i, $j ];

    return [ $player, $opponent ];
}


sub row_reduce
{
    my ($self) = @_;

    my @spliced;

    my $rsize = @{ $self->{payoff} } - 1;
    my $csize = @{ $self->{payoff}[0] } - 1;

    for my $row ( 0 .. $rsize )
    {
#warn "R:$row = @{ $self->{payoff}[$row] }\n";
        for my $r ( 0 .. $rsize )
        {
            next if $r == $row;
#warn "\tN:$r = @{ $self->{payoff}[$r] }\n";
            my @cmp;
            for my $x ( 0 .. $csize )
            {
                push @cmp, ( $self->{payoff}[$row][$x] <= $self->{payoff}[$r][$x] ? 1 : 0 );
            }
#warn "\t\tC:@cmp\n";
            if ( all { $_ == 1 } @cmp )
            {
                push @spliced, $row;
            }
        }
    }

    $self->_reduce_game( $self->{payoff}, \@spliced, 1 );

    return $self->{payoff};
}


sub col_reduce
{
    my ($self) = @_;

    my @spliced;

    my $transposed = transpose( $self->{payoff} );

    my $rsize = @$transposed - 1;
    my $csize = @{ $transposed->[0] } - 1;

    for my $row ( 0 .. $rsize )
    {
#warn "R:$row = @{ $transposed->[$row] }\n";
        for my $r ( 0 .. $rsize )
        {
            next if $r == $row;
#warn "\tN:$r = @{ $transposed->[$r] }\n";
            my @cmp;
            for my $x ( 0 .. $csize )
            {
                push @cmp, ( $transposed->[$row][$x] >= $transposed->[$r][$x] ? 1 : 0 );
            }
#warn "\t\tC:@cmp\n";
            if ( all { $_ == 1 } @cmp )
            {
                push @spliced, $row;
            }
        }
    }

    $self->_reduce_game( $transposed, \@spliced, 2 );

    $self->{payoff} = transpose( $transposed );

    return $self->{payoff};
}

sub _reduce_game
{
    my ( $self, $payoff, $spliced, $player ) = @_;

    my $seen = 0;
    for my $row ( @$spliced )
    {
        $row -= $seen++;
        # Reduce the payoff column
        splice @$payoff, $row, 1;
        # Eliminate the strategy of the opponent
        delete $self->{$player}{$row + 1} if exists $self->{$player}{$row + 1};
    }
}


sub mm_tally
{
    my ($self) = @_;

    my $mm_tally;

    if ( $self->{payoff1} && $self->{payoff2} )
    {
        # Find maximum of row minimums for the player
        $mm_tally = $self->_tally_max( $mm_tally, 1, $self->{payoff1} );

        # Find minimum of column maximums for the opponent
        my @m = ();
        my %s = ();

        my $transposed = transpose( $self->{payoff2} );

        for my $row ( 0 .. @$transposed - 1 )
        {
            $s{$row} = min @{ $transposed->[$row] };
            push @m, $s{$row};
        }

        $mm_tally->{2}{value} = max @m;

        for my $row ( sort keys %s )
        {
            push @{ $mm_tally->{2}{strategy} }, ( $s{$row} == $mm_tally->{2}{value} ? 1 : 0 );
        }
    }
    else
    {
        # Find maximum of row minimums
        $mm_tally = $self->_tally_max( $mm_tally, 1, $self->{payoff} );

        # Find minimum of column maximums
        my @m = ();
        my %s = ();

        my $transposed = transpose( $self->{payoff} );

        for my $row ( 0 .. @$transposed - 1 )
        {
            $s{$row} = max @{ $transposed->[$row] };
            push @m, $s{$row};
        }

        $mm_tally->{2}{value} = min @m;

        for my $row ( sort keys %s )
        {
            push @{ $mm_tally->{2}{strategy} }, ( $s{$row} == $mm_tally->{2}{value} ? 1 : 0 );
        }
    }

    return $mm_tally;
}

sub _tally_max
{
    my ( $self, $mm_tally, $player, $payoff ) = @_;

    my @m;
    my %s;

    # Find maximum of row minimums
    for my $row ( 0 .. @$payoff - 1 )
    {
        $s{$row} = min @{ $payoff->[$row] };
        push @m, $s{$row};
    }

    $mm_tally->{$player}{value} = max @m;

    for my $row ( sort keys %s )
    {
        push @{ $mm_tally->{$player}{strategy} }, ( $s{$row} == $mm_tally->{$player}{value} ? 1 : 0 );
    }

    return $mm_tally;
}


sub pareto_optimal
{
    my ($self) = @_;

    my $pareto_optimal;

    my $rsize = @{ $self->{payoff1} } - 1;
    my $csize = @{ $self->{payoff1}[0] } - 1;

    # Compare each row & column with every other
    for my $row ( 0 .. $rsize )
    {
        for my $col ( 0 .. $csize )
        {
#warn "RC:$row,$col = ($self->{payoff1}[$row][$col],$self->{payoff2}[$row][$col])\n";

            # Find all pairs to compare against
            my %seen;
            for my $r ( 0 .. $rsize )
            {
                for my $c ( 0 .. $csize )
                {
                    next if ( $r == $row && $c == $col ) || $seen{"$r,$c"}++;

                    my $p = $self->{payoff1}[$row][$col];
                    my $q = $self->{payoff2}[$row][$col];
#warn "\trc:$r,$c = ($self->{payoff1}[$r][$c],$self->{payoff2}[$r][$c])\n";

                    if ( $p >= $self->{payoff1}[$r][$c] && $q >= $self->{payoff2}[$r][$c] )
                    {
#warn "\t\t$row,$col > $r,$c at ($p,$q)\n";
                        # XXX We exploit the unique key feature of perl hashes
                        $pareto_optimal->{ "$row,$col" } = [ $p, $q ];
                    }
                }
            }
        }
    }

    return $pareto_optimal;
}


sub nash
{
    my ($self) = @_;

    my $nash;

    my $rsize = @{ $self->{payoff1} } - 1;
    my $csize = @{ $self->{payoff1}[0] } - 1;

    # Find all row & column max pairs
    for my $row ( 0 .. $rsize )
    {
        my $rmax = max @{ $self->{payoff2}[$row] };

        for my $col ( 0 .. $csize )
        {
#warn "RC:$row,$col = ($self->{payoff1}[$row][$col],$self->{payoff2}[$row][$col])\n";

            my @col;
            for my $r ( 0 .. $rsize )
            {
                push @col, $self->{payoff1}[$r][$col];
            }
            my $cmax = max @col;

            my $p = $self->{payoff1}[$row][$col];
            my $q = $self->{payoff2}[$row][$col];

            if ( $p == $cmax && $q == $rmax )
            {
#warn "\t$p == $cmax && $q == $rmax\n";
                $nash->{"$row,$col"} = [ $p, $q ];
            }
        }
    }

    return $nash;
}


sub play
{
    my ( $self, %strategies ) = @_;

    my $play;

    # Allow for alternate strategies
    $self->{$_} = $strategies{$_} for keys %strategies;

    my $rplay = $self->_player_move(1);
    my $cplay = $self->_player_move(2);

    $play->{ "$rplay,$cplay" } = exists $self->{payoff} && $self->{payoff}
        ? $self->{payoff}[$rplay - 1][$cplay - 1]
        : [ $self->{payoff1}[$rplay - 1][$cplay - 1], $self->{payoff2}[$rplay - 1][$cplay - 1] ];

    return $play;
}

sub _player_move {
    my ( $self, $player ) = @_;

    my $keys    = [ sort keys %{ $self->{$player} } ];
    my $weights = [ map { $self->{$player}{$_} } @$keys ];

    # Handle the [0, 0, ...] edge case
    $weights = [ (1) x @$weights ] if 0 == sum0 @$weights;

    return choose_weighted( $keys, $weights );
}

1;

__END__