Today marks the 20th anniversary of Doom, a game I feel has played a major role in my choice to become a programmer. I remember the days well of firing up DeHackEd and WAD Author and making small checks, and the joy seeing my changes right there in front of me, ready to interact with in realtime. Later, I went on to learn how to do game programming, and as they say - the rest is history. It seems fitting today that we look at another library that can be useful for interactive multimedia programming, and that library is
Created by Ben Lippmeier (who is also known for his work on
gloss is a high-level library for drawing vector graphics and dealing with interactions, with the aim of “getting something cool on the screen in under 10 minutes”.
gloss comes with abstractions for mixing colours, creating displays, dealing with input, and drawing basic primitives - such as lines, circles, bitmaps, text, and so on. Today, we’ll look at creating a simple Tic-tac-toe game with a little bit of artificial “intelligence”.
The first thing we need to do is to get a window created to display our game.
gloss has a few options for this, depending on what you’re trying to display. A simulation is essentially a movie that cannot be interacted with that has a fixed timestep, where as an animation is similar but has a variable timestep. We want interactivity though, so we’ll use the “Game” mode. The main function here is
playIO takes a few initial configuration options - the type of display to create, the target framerate, the background colour and the initial state of the world (whatever that may be). Our state of the world can be a marker of whose turn it is, and the current board configuration. The board configuration itself is just a list of list of plays, where the initial state is a board that has no plays.
Now we’re in a position to create a window and start working on our game:
We create a new window with a title, our initial state of an empty board with “X” is next to play, and “azure” as the background colour. We have to write three functions now -
drawBoard is straight forward:
drawBoard :: (Board, Play) -> IO Picture drawBoard (board, _) = return (grid <> plays) where grid = color black (line [ (-100, -300), (-100, 300) ]) <> color black (line [ ( 100, -300), ( 100, 300) ]) <> color black (line [ (-300, 100), ( 300, 100) ]) <> color black (line [ (-300, -100), ( 300, -100) ]) plays = mconcat [ translate (fromIntegral $ (x - 1) * 200) (fromIntegral $ (y - 1) * 200) $ case play of X -> color white (thickCircle 1 50) O -> color black (thickCircle 1 50) | x <- [0..2] , y <- [0..2] , Just play <- [ (board !! x) !! y ] ]
drawBoard needs to return a
Picture, which is the type of primitives that
gloss can display.
Pictures along with composition form a
Monoid, which means we can easily draw a complex scene by combining simpler
Pictures together. In this case, I begin by simply declaring that I want to draw both the grid and the current plays. The grid is defined to be the combination of 4 lines (two vertical, two horizontal), while the plays is a little more involved.
To draw the plays, I loop over every cell in the board by the cell’s coordinates - I’ll be using the coordinates to work out the translation to draw the play. We loop over all the coordinates, and attempt to pattern match that cell against
Just play. If this fails, the list comprehension will continue, but if it does succeed, then we can draw a single play in the game. This list comprehension produces a list of plays, which I can then
mconcat together - turning my
[Picture] into a single
So far so good! But what about playing the game? The next piece of the puzzle is getting some input, and we can do this with
handleInput takes an
Event and the state of the world, and can respond to that event by producing a new state. We’re only interested in a specific event - the release of the left mouse button to signify the user wants to make a move. We need to be careful though - the user should only be able to make moves if it’s their go! That’s why we have the play marker in the game state. We’ll deal the case where it’s our turn first:
We use pattern matching in the
handleInput parameters to make sure it’s “X”s turn, and also that the event is the release of the left mouse button. The next thing we need to do is convert the mouse coordinates to grid coordinates, and then we look up those coordinates against our current state. If someone has already played there then we don’t make any changes - otherwise we return an updated board with an “X” wherever the user clicked, and switch over to “O”s turn:
We’re almost there! The final function to implement is just one to step the game at our framerate - 10 frames a second, as specified in the call to
playIO. In this case, there’s not really anything to do, so for now we’ll just act as identity:
Our game isn’t very fun right now - once the user clicks on a space we make a move and switch over to “O”s move - but there is no player “O”! Let’s rectify that with some fairly brain dead AI.
My plan here is to use Haskell’s lightweight threading to fork off an AI thread that will make a choice of which move to play. Because we have a lightweight thread, we can easily use
threadDelay to give the illusion that the computer is “thinking”. Two functions will need to change with the addition of AI -
handleInput will need indicate that AI needs to play a move, and
stepGame is going to need to check if the AI has made a move.
I’ll use a
MVar Board to keep track of the AI. Initially, this
MVar is empty - there is no value inside it. When the player makes a move, we fork an AI thread with the new board configuration, and the AI will place a further new board in the
MVar, containing its response.
stepGame will then be responsible for interleaving all this threading. First, lets have a look at our AI function:
forkAi :: MVar Board -> Board -> IO () forkAi aiMove board = void $ forkIO $ do -- Pause while we think what to do randomRIO (100000, 1000000) >>= threadDelay -- Choose a random move let plays = [ (ix x . ix y .~ Just O) board | x <- [0..2] , y <- [0..2] , Nothing <- [ (board !! x) !! y ] ] case plays of  -> do -- There are no more moves! putMVar aiMove board _ -> do -- Respond with the move chosen at random newBoard <- (plays !!) <$> randomRIO (0, length plays - 1) putMVar aiMove newBoard
The first thing we do is use
threadDelay to slow the AI down. Once the delay has passed we build a list of all possible avenues from the current board configuration. Then we take a random move and respond with that. (There’s also a little bit of checking to make sure we’re not in the scenario where there are no more moves left).
We hook this into
handleInput by calling
forkIO before we return a new board:
stepGame needs to check if the AI has played their move, so this function gets a little more complex now:
If it’s “O”s go, we use
tryTakeMVar to optimistically check if the AI has made a move. If they have, we’ll have a
Just Board to use as our new game state. Otherwise, we’ll get
Nothing back - which means that the AI hasn’t made a choice yet so we should keep the state the same. Here’s what we get in the end:
gloss is a really fun game programming library, mainly because it really stays out of the way. As I quoted in the opening paragraphs,
gloss wants to help you get things on the screen as fast as possible, and I think it definitely achieves that. The code I wrote today is hardly production grade Haskell, but it doesn’t matter, because it was fun to write. I think when it comes to doing creative work in Haskell, fun has to come first, as that’s where the drive to keep going comes from. This doesn’t mean
gloss requires you to write bad code either - but it lets you defer the choices of being “correct” until a later stage.
If you want to take this code a little further, then feel free to grab my work from Github! As you will have noticed from the above video, the game doesn’t have any concept of scoring or the end of a game, which is certainly where work needs to focus. But you might also want to have a play by changing
drawBoard to be closer to the classic game using X and O.
You can contact me via email at email@example.com or tweet to me @acid2. I share almost all of my work at GitHub. This post is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
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