```Luke Cowell and Chris Cacciatore both submitted solutions for this
week's quiz. There was some ambiguity in the way the quiz was posted,
so the implementations were slightly different from one another. Luke
had a running total for each player and Chris had a single total.
Despite that difference, both solutions tackled the problem similarly
and are both interesting.

The `Dice` classes in both solutions have methods for rolling a random
side and validating moves by keeping track of opposites. Chris keeps
an array of explicitly defined opposites: `@opposites =
[[1,6],[2,5],[3,4]]`. Luke's method for determining available moves
makes use of the fact that opposites are defined by the faces adding
up to seven:

def available_nums
(1..@total_sides).reject {|n| (@top + n == (@total_sides + 1) || n == @top)}
end

Each of these implementations has a different strength when it comes
to future changes: Chris's is easier to rearrange the configuration of
the dice and Luke's is easier to expand to dice with a different
number of faces. One caveat for dice of more faces is that additional
adjacency information would need to be added (for example a
dodecahedron or icosahedron would have different adjacencies).

Both solutions require the definition of only one method to create a
new player or different AI. For Luke's code the only method that needs
to be implemented is `next_move`. Let's take a look at the `Human` and
`Computer` `Player` implementations:

class Human < Player
def next_move(dice, opponents = nil)
done = false
while(done == false)
choice = gets.to_i
if(dice.valid?(choice) == true)
done = true
else
print "!!!you can't choose #{choice}!!!"
end
puts
end

choice
end
end

For the human player it gets the choice from the prompt, prompting
again if the player selects an invalid choice.

class Computer < Player
def next_move(dice, opponents = nil)
if(@score == 30)
return 1
elsif((@score % 6) == 0) && dice.available_nums.include?(6)
return 6
else
return dice.available_nums[rand(4)]
end
end
end

The computer player tries to set up a path for a win. If the score is
a multiple of 6 and the computer is able to choose 6 on the die, then
it will choose 6 each time until the score reaches 30, and then will
choose 1 on the next turn to secure victory. If it can't then it makes
a random choice. It would be fairly easy to implement different
computer AI by providing different ways to compute the next move.

Chris uses a similar technique for choosing the next move from the
computer player. It checks for a winning move and takes it if
available, otherwise it makes a random move.

def choose_move(score)
sleep(1)
if score < 25
while !@die.legal_move?( (r = rand(6)+1) )
end
return r
else
#simple win
return 31-score if @die.legal_move?(31-score)
return rand(6)+1
end
end

The play consists of players alternating moves. Both programs check
for the validity of the move outside of the player's implementation,
so you are unable to cheat by having your player return a roll of `(31
- current_value)`.

An interesting element of Luke's program is that he allows you to set
up a game between two human players or two computer players rather
than just between a human and a computer.

Though the specific game mechanics were slightly different in each
program, they both provided interesting solutions to the problem.

Thank you Luke and Chris for your submissions to this week's quiz!

--
-Daniel
http://rubyquiz.strd6.com

```