Introduction to AI for game programming students

I was recently invited to give a talk on “AI in games” to Jyväskylä’s AMK game programming students. The lecture could have gone better if I had prepared more material for it, but the catch was that I didn’t know what to prepare. These notes act as a guide for “next time”. I won’t go into any depth on the subjects here.

  1. Briefly introduce scientific AI, point out useful libraries [A*, speech recognition, opencv] then waft it away
  2. Focus on architecture of players, representation of game state and move logic
  3. Establish the simplest AI player for tic-tac-toe, then develop it to a perfect player [“smart as possible AI”]
  4. Make the tic tac toe player more fun to play against
  5. Consider expanding it to more complex games (chess, civilization) and optimizations
  6. Human behavior simulation – know the limits of senses, program them in. FPS/Stealth AI is a good example. [“dumb as a human AI”]
  7. Planning and decision making architecture
  8. Techniques for more realistic behavior

Additionally…

  • Examples of AI in video games: planner in fear, neural networks aren’t used much in industry (notable exception, Supreme Commander 2) and only for decisions, Quake 3 doesn’t have neural net bots
  • Data structures and algorithms are ever useful
  • Observe nature and mimic behaviour
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