Google AI Challenge 2010
Friday, December 3rd, 2010
A game being played in the Google AI Challenge 2010
Well, the google AI challenge is over and my bot finished 1143th out of 4617. That’s a bit of an underwhelming finish, I agree, but there’s more to tell. Given the game the bots were to play and the severe time restrictions the bots had to choose a move each turn, the challenge was dominated by, what I call, tactics bots. That is, they rely on hand-coded tactics based on the programmers expertise on the game. The design cycle goes a bit like this:
- Designer reflects on how they play the game and thinks up a way to codify a way to choose good moves
- Implement the idea
- Play the bot against others and see how it does
- Reflect again and think of new information to consider when choosing good moves and how it can be integrated with the previous ideas
- Goto step 2
I don’t mean to denigrate this approach, it is the basic premise of every bot AI from a commercial video game, that I’ve seen the code for. This approach often yields a bot that scores very well on the (very technical) goodness vs. time per move metric.







Beyond aesthetics, Video game art serves an important functional purpose. It creates the context in which the game happens. This context allows the player to draw upon their experience in the real world to gain insight into the game. For example, the image to the right from Mystery House doesn’t provide much information about what the house looks like. The player can’t see what colour it is, whether the paint is peeling, whether it is brick or has painted siding. But it taps into the player’s real world experience with houses and empowers the player to imagine those details by drawing from their experience.