Micael DaGraca - Practical Game AI Programming

• 1: Different Problems Require Different Solutions
  • b'Chapter 1: Different Problems Require Different Solutions'
  • b'A brief history of and solutions to\xc3\x82\xc2\xa0game AI'
  • b'Enemy AI in video games'
  • b'From simple to smart and human-like AI'
  • b'Visual and audio awareness'
  • b'Summary'

• 2: Possibility and Probability Maps
  • b'Chapter 2: Possibility and Probability Maps'
  • b'Game states'
  • b'Possibility maps'
  • b'Defining the states'
  • b'Probability maps'
  • b'Summary'

• 3: Production System
  • b'Chapter 3: Production System'
  • b'Automated finite-state machines (AFSMs)'
  • b'Utility-based functions'
  • b'Dynamic game AI balancing'
  • b'Summary'

• 4: Environment and AI
  • b'Chapter 4: Environment and AI'
  • b'Visual interactions'
  • b'Basic environment interactions'
  • b'Advanced environment interactions'
  • b'Summary'

• 5: Animation Behaviors
  • b'Chapter 5: Animation Behaviors'
  • b'2D animation versus 3D animation'
  • b'Animation state machines'
  • b'Smooth transitions'
  • b'Summary'

• 6: Navigation Behavior and Pathfinding
  • b'Chapter 6: Navigation Behavior and Pathfinding'
  • b'Navigation behavior'
  • b'Summary'

• 7: Advanced Pathfinding
  • b'Chapter 7: Advanced Pathfinding'
  • b'Simple versus advanced pathfinding'
  • b'A* search algorithm'
  • b'Summary'

• 8: Crowd Interactions
  • b'Chapter 8: Crowd Interactions'
  • b'What is crowd interaction'
  • b'Video games and crowd interactions'
  • b'Planning crowd interactions'
  • b'Crowd collision avoidance'
  • b'Summary'

• 9: AI Planning and Collision Avoidance
  • b'Chapter 9: AI Planning and Collision Avoidance'
  • b'Search'
  • b'Summary'

• 10: Awareness
  • b'Chapter 10: Awareness'
  • b'Stealth sub-genre'
  • b'About tactics'
  • b'About awareness'
  • b'Implementing vision awareness'
  • b'Summary'

To better understand how to overcome the problems that game developers are currently facing, we need to dig a little bit into the history of video game development and take a look at the problems and their solutions that were so important at the time. Some of them were so avant-garde that they actually changed the entire history of video game design itself, and we still use the same methods today to create unique and enjoyable games.

One of the first relevant marks that is always worth mentioning when talking about game AI is computer chess programmed to compete against humans. It was the perfect game to start experimenting with artificial intelligence, because chess usually requires a lot of thought and planning ahead, something that a computer couldn't do at the time because it was necessary to have human features in order to successfully play and win the game. So, the first step was to make it able for the computer to process the game rules and think for itself in order to make a good judgement of the next move that the computer should do to achieve the final goal, that is, winning by checkmating. The problem is that chess has many possibilities; so, even if the computer had a perfect strategy to beat the game, it was necessary to recalculate that strategy, adapting it, changing, or even creating a new one every time something went wrong with the first strategy.

Humans can play differently every time; this makes it a huge task for the programmers to input all the possible data into the computer in order to win the game. So, writing all the possibilities that could exist wasn't a viable solution, and because of that, the programmers needed to think again about the problem. Then, one day, they finally came out with a better solution, that is, to make the computer decide for itself every turn, choosing the most plausible option for each turn; that way, the computer could adapt to any possibility in the game. Yet, this involved another problemthe computer would only think the short-term moves, and not create any plans to defeat the human in the future moves; so, it was easy to play against it, but at least we started to have something going on. It was decades later that someone defined the word Artificial Intelligence ( AI ) by solving the first problem that many researchers had by trying to create a computer that was capable of defeating a human player. Arthur Samuel is the person responsible for creating a computer that could learn for itself and memorize all the possible combinations. That way, there wasn't necessarily any human intervention and the computer could actually think on its own, and that was a huge step that is still impressive even by today's standards.