It’s time for a small post again. I haven’t updated my blog for a while, but for a reason: there hasn’t really been anything interesting to write about lately. Don’t worry, I’ve been working on my project, but rather implementing it than designing it. The last time I wrote about AI and mentioned it’d be the next thing to implement for Freekick. Well, the basics of AI are there, as well as the basics of everything else (server + client + the organizatory part). I’ve spent the last month writing the AI, writing a client (i.e. a window to the soccer pitch) and making sure the thing doesn’t crash by itself. Sounds like a 0.0.1 release, doesn’t it? Yeah, we’re that far already.
To the disappointment of neural network fans I haven’t implemented them at all in Freekick AI, not yet. The basic structure of the AI is slowly coming together, and when I can concentrate on the details, I’ll try and make some use of neural networks. At the moment, however, the AI follows simple logic for decision making that will be refined later. Having a simplified AI at this stage is helpful because it lets me concentrate on figuring out the bigger picture of the AI functionality.
The current AI is roughly split into two parts, one that defines the possible actions and another that compares these actions with each other and chooses between them. Here, defining the possible actions also includes a set of helper functions such as for finding the best spots on the pitch for scoring or the chances of a successful pass to a teammate.
Splitting the AI code like this makes maintaining it easier than if it was one bloated, monolithic monster. Improving the code should also be simpler in the long run, because if the two parts only communicate via clearly defined interfaces, one part could be swapped or reworked without interfering with the other part. This way I can first make things run with simple logic and when the AI starts to seem too stupid replacing parts of it with, say, neural networks shouldn’t be a big problem. At the moment, though, the AI code is rather transparent (with 10 files and 400 lines of Haskell code), but when the code grows, it will be necessary to make this division even clearer.
I then went on to write an SDL client for Freekick. It’s actually a bit early to call it a client, since there is no single player (nor multi player) mode and the client doesn’t control a player but merely spectates the match, but for now it’s enough to see what the AI is doing. A simple single player mode with some awkward controls will be added later. The client is very ugly, though, and thereby reflects my artistic skills rather perfectly. Here’s a screen shot.
Soccer in all its beauty.
Here it probably starts to become clear for everyone why I wanted Freekick to be so modular. The client is just a client, its duties are merely receiving the match status from the server and displaying it as it sees fit, as well as taking input from the player. It can be exchanged or rewritten in another language without the need to touch the rest of the game logic. I’m also planning on writing an ncurses client for use in non-graphical environments (as if the SDL client wasn’t ugly enough).
As for the server (i.e. the code that handles the network, communication, enforces soccer rules and world physics), it’s running with no major problems. Minor problems include network code that has problems handling disconnecting clients and relatively inaccurate physics, but for now it’s adequate. Probably the biggest thing that differentiates Freekick from a real alpha version of a very ugly spectator only soccer game is (along with the fact that the match actually never ends) that there is actually no connection between the “organizatory part” (i.e. choosing two clubs that play a friendly game against each other, or starting a knockout tournament) and the actual, viewable match.
This all means there is still some more work to do before Freekick could be considered usable. But in the spirit of “Release early, release often” I’m giving you the code (written in Haskell as usual) already anyways. If you have darcs, the easiest way to the code is “darcs get http://code.haskell.org/freekick/”, but there are also tarballs of the code as well of a binary version (x86, Linux) at http://finder.homelinux.org/freekick/files/. With enough playing around one might be able to start the thing, but I’ll write here the way it’s supposed to work anyway. First you start the server (“physics”) with a matchdata file (“matchdata.md”) as parameter. Then you start both the client and the AI, which both connect to the server. AI interprets the information from the server and sends the desired player actions to it. The client displays the players in all its SDL glory. And voila, you’re witnessing a soccer AI experiment.
From the issues mentioned above, the ones I’ll be concentrating on in the near future will be the ability to actually play the game and control a player, finishing up the match flow (i.e. ending the match at some point), and tying the organizatory part together with the match part. After these steps, it’s probably time for some polish, like a main menu, configuration options and a prettier client. As for the 0.0.2 release, it’ll be available, soon. I’ll keep you posted.