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英文版 Chapter 1, Introduction to Game AI Here, we define game AI and discuss the current state of the art as well as the future of this technology. Chapter 2, Chasing and Evading We cover basic techniques for chasing and evading as well as more advanced techniques for intercepting. We also cover techniques applicable to both tile-based and continuous game environments. Chapter 3, Pattern Movement Pattern movement techniques are common to many video games and developers have been using them since the early days of gaming. You can use these techniques to preprogram certain behaviors such as the patrolling of a guard or the swooping in of a spacecraft. Chapter 4, Flocking The flocking method we examine in this chapter is an example of an A-life algorithm. In addition to creating cool-looking flocking behavior, A-life algorithms form the basis of more advanced group movement. Chapter 5, Potential Function Based Movement Potential-based movement is relatively new in game AI applications. The cool thing about this method is that it can handle chasing, evading, swarming, and collision avoidance simultaneously. Chapter 6, Basic Pathfinding and Waypoints Game developers use many techniques to find paths in and around game environments. In this chapter, we cover several of these methods, including waypoints. Chapter 7, A* Pathfinding No treatment of pathfinding is complete without addressing the workhorse algorithm of pathfinding; therefore, we devote this whole chapter to the A* algorithm. Chapter 8, Scripted AI and Scripting Engines Programmers today often write scripting engines and hand off the tools to level designers who are responsible for creating the content and defining the AI. In this chapter, we explore some of the techniques developers use to apply a scripting system in their games, and the benefits they receive. Chapter 9, Finite State Machines Finite state machines are the nuts and bolts of game AI. This chapter discusses the fundamentals of finite state machines and how to implement them. Chapter 10, Fuzzy Logic Developers use fuzzy logic in conjunction with or as a replacement for finite state machines. In this chapter, you'll learn the advantages fuzzy techniques offer over traditional logic techniques. Chapter 11, Rule-Based AI Technically, fuzzy logic and finite state machines fall under the general heading of rules-based methods. In this chapter, we cover these methods as well as other variants. Chapter 12, Basic Probability Game developers commonly use basic probability to make their games less predictable. Such cheap unpredictability enables developers to maintain substantial control over their games. Here, we cover basic probability for this purpose as well as lay the groundwork for more advanced methods. Chapter 13, Decisions Under Uncertainty—Bayesian Techniques Bayesian techniques are probabilistic techniques, and in this chapter we show how you can use them for decision making and for adaptation in games. Chapter 14, Neural Networks Game developers use neural networks for learning and adaptation in games—in fact, for anything from making decisions to predicting the behavior of players. We cover the most widely used neural network architecture, in detail. Chapter 15, Genetic Algorithms Genetic algorithms offer opportunities for evolving game AI. Although developers don't often use genetic algorithms in games, their potential for specific applications is promising, particularly if they are combined with other methods.