發(fā)布時間：2018-08-06 07:53

【摘要】： 隨著網(wǎng)絡(luò)游戲逐漸融入人們的娛樂生活,人們對在網(wǎng)絡(luò)游戲中的虛擬體驗(yàn)有了更高的要求。以往流行的單純打怪,過關(guān),升級的模式已不能吸引更多的玩家。網(wǎng)絡(luò)游戲行業(yè)迫切需要更真實(shí),更具有挑戰(zhàn)性的對手。我認(rèn)為,在未來的幾年里,AI技術(shù)將飛速發(fā)展,像Black White和Hello這樣的游戲已經(jīng)讓我們?yōu)槠銩I技術(shù)而驚嘆。游戲玩家正期待出現(xiàn)更多這樣的游戲。對于游戲Al引擎也曾有人提出利用遺傳算法和神經(jīng)網(wǎng)絡(luò)來實(shí)現(xiàn),但是這兩種人工智能技術(shù)極其復(fù)雜,需要占用大量的CPU時間。因此在快速動作的游戲世界,這兩種技術(shù)并不適用�，F(xiàn)在比較流行的實(shí)現(xiàn)游戲AI的技術(shù)是有限狀態(tài)機(jī)(FSM)。有限狀態(tài)機(jī)是一種基于規(guī)則—行動的處理模式,因?yàn)樗唵巍⒅庇^、容易修改,所以得到了廣泛應(yīng)用。但是基于有限狀態(tài)機(jī)的AI引擎通常造成游戲角色的非智能行為,比如說：多個非玩家角色(NPC)占用同一路線,造成路徑堵塞；怪獸不懂得協(xié)同作戰(zhàn)等。本文就是在此現(xiàn)狀下提出來了一種新的人工智能引擎實(shí)現(xiàn)方法—基于決策模型的人工智能引擎。它比傳統(tǒng)的基于有限狀態(tài)機(jī)的人工智能引擎更加先進(jìn)。它使游戲里面的怪獸(MC)和非玩家角色(NPC)能夠在不同的情況下做出最有效最理智的決策,使游戲玩家沉浸在一個比較真實(shí)的游戲世界里面。 本文結(jié)構(gòu)如下：第一章介紹了游戲引擎基本組成及發(fā)展情況,AI引擎在游戲中所處的地位及作用等。第二章講述傳統(tǒng)基于有限狀態(tài)機(jī)的AI引擎設(shè)計模式,建立了一個有限狀態(tài)機(jī)的類。第三章講述本文提出的基于決策模型的AI引擎設(shè)計模式及游戲?qū)嵗５谒恼卤容^兩種人工智能游戲引擎的利與弊,著重闡述了基于決策模型的AI引擎的優(yōu)勢所在。第五章通過將把兩種AI引擎分別應(yīng)用到游戲?qū)嵗?來比較它們之間的差別。第六章總結(jié)全文并對人工智能引擎的發(fā)展方向做出了一個預(yù)測。
[Abstract]:With the gradual integration of online games into people's entertainment life, people have higher requirements for virtual experience in online games. In the past popular pure fight strange, pass, upgrade the mode can not attract more players. The online game industry urgently needs more real, more challenging opponents. I think that in the next few years, the AI technology will grow rapidly, and games like Black White and Hello have made us marvel at its AI technology. Gamers are expecting more of these games. For the game's Al engine, it has been proposed to use genetic algorithm and neural network, but these two artificial intelligence technologies are extremely complex, which require a lot of CPU time. So in the world of fast action games, these two technologies don't work. The most popular technology to implement game AI is the finite state machine (FSM). Finite state machine (FSM) is a rule-action-based processing model, which is widely used because it is simple, intuitive and easy to modify. But the AI engine based on the finite state machine usually causes the non-intelligent behavior of the game characters, such as: many non-player characters (NPC) occupy the same route, resulting in path blockage; the monster does not know how to cooperate in combat, and so on. In this paper, a new implementation method of artificial intelligence engine based on decision model is proposed. It is more advanced than the traditional artificial intelligence engine based on finite state machine. It enables the game's monster (MC) and the non-player character (NPC) to make the most effective and rational decisions in different situations and immerse the gamer in a more real game world. The structure of this paper is as follows: the first chapter introduces the basic composition and development of game engine and the position and function of AI engine in the game. The second chapter describes the traditional AI engine design pattern based on finite state machine, and establishes a class of finite state machine. The third chapter describes the AI engine design pattern and game examples based on decision model. Chapter 4 compares the advantages and disadvantages of the two artificial intelligence game engines, focusing on the advantages of AI engine based on decision model. Chapter 5 compares the two AI engines by applying them to game instances. The sixth chapter summarizes the full text and makes a prediction to the development direction of artificial intelligence engine.
【學(xué)位授予單位】：暨南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2010
【分類號】：TP391.3

【引證文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 張時銘;短道速滑仿真系統(tǒng)中智能體決策過程的研究與實(shí)現(xiàn)[D];哈爾濱工業(yè)大學(xué);2011年

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本文編號：2167022