游戲ai介紹(doc)-在線瀏覽
2024-08-05 03:19本頁面
【正文】 ，大多數(shù)游戲都包含一些人工智能（AI）的運(yùn)用。各種各樣的游戲類型和游戲人物對什么事游戲AI給出了一個(gè)相當(dāng)廣泛的解釋。Some developers consider tasks such as pathfinding as part of game AI. Some developers even consider collision detection to be part of game AI. Clearly, some wideranging interpretations of game AI exist. We39。顯然，廣泛的游戲AI解釋是存在的。游戲AI屬于弱AI的范疇是最適合的，但是，在某個(gè)意義上，你可以認(rèn)為游戲AI有更廣泛的術(shù)語。t always interested in giving nonplayer characters humanlevelintellect. Perhaps we are writing code to control nonhuman creatures such as dragons, robots, or even rodents. Further, who says we always have to make nonplayer characters smart? Making some nonplayer characters dumb adds to the variety and richness of game content. Although it is true that game AI is often called upon to solve fairly plex problems, we can employ AI in attmepts to give nonplayer characters the appeatance of having different personalities, or of portraying emotions or various dispositions for example, scared, agitated, and so on.在游戲中，我們不一定對給參與游戲的機(jī)器方以人水平的智能感興趣。另外，誰說我們必須讓機(jī)器方更聰明呢？我們可以添加一些啞巴的機(jī)器方以增加游戲內(nèi)容的多樣性和豐富性。The bottom line is that the definition of game AI is rather broad and flexible. Any thing that gives the illusion of intelligence to an appropriate level, thus making the game AI more immersive ,challenging,and most importantly,fun,can be considered game AI.Just like the use of real physics in games, good AI adds to the immersiveness of the game, drawing palyers in and suspending their reality for a time.游戲AI底線的定義是相當(dāng)廣泛和靈活的。正像在游戲中使用真實(shí)的物理現(xiàn)象那樣，優(yōu)良的AI增加了游戲的沉浸性，吸引游戲者，使他們一度置身于虛擬世界中。Deterministic behavior or performance is specified and predictable. There39。s x and y coordinates coincide with the target location.定性的行為表現(xiàn)是具有指定和可預(yù)見性。一個(gè)簡單的追逐算法就是定性行為的一個(gè)例子。Nondeterministic behavior is the opposite of deterministic behavior. Behavior has a degree of uncertainty and is somewhat unpredictable( the degree of uncertainty depends on the AI method employed and how well that method is understood). An example of nondeterministic behavior is a nonplayer character learning to adapt to the fighting tactics of player. Such learning could use a neural network, a Bayesian trchnique, or a genetic algorithm.非定性行為和定性行為正好相反。機(jī)器方學(xué)習(xí)并適應(yīng)玩家的戰(zhàn)斗策略就是一個(gè)非定性行為的例子。Deterministic AI techniques are the bread and butter of game AI. These teachniques are predictable, fast, and easy to implement, understand, test, and debug. Although they have a lot going for them, deterministic methods place 寄予the burden of anticipating（預(yù)料 期望） all scenarios （方案、情節(jié)，情景）and coding all behavior explicitly明確的 on the developers39。s playlife, so to speak.定性AI技術(shù)是游戲AI的基礎(chǔ)。盡管這種技術(shù)很成熟，開發(fā)者還是需要編寫數(shù)量非常巨大的情節(jié)腳本以及各種行為。Nondeterministic methods facilitate learning and unpredictable gameplay. Further, developers don39。ll consider in this book are good examples of emergent behavior.非定性的方法讓游戲的不可預(yù)測性和不確定性大大增加。非定性方法也可以獨(dú)立的學(xué)習(xí)和推斷，他們可以能夠自行生產(chǎn)處理突發(fā)狀況的即時(shí)行為，或者自行產(chǎn)生沒有明確被指令指示的行為。Developers traditionally have been a bit wary of AI that is nondeterministic, although this is changing. Unpredictability is diffcult to test and debughow can you test all possible variations of player action to make sure the game doesn39。非定性AI所產(chǎn)生的不確定性是難以測試和調(diào)試的你怎么確定玩家的各種操作不會(huì)讓游戲在某些情況下產(chǎn)生愚蠢的行為呢？游戲開發(fā)者們面臨不斷縮短的開發(fā)周期，這樣不斷縮短的開發(fā)周期使開發(fā)和測試產(chǎn)品就緒標(biāo)準(zhǔn)新技術(shù)特別困難。At least until recently, another factor that has limited game
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