臺灣博碩士論文加值系統

隨著硬體與軟體進步，遊戲人工智慧在電子遊戲中扮演越來越重要的角色，一個好的人工智慧可以讓遊戲表現的更出色、豐富。而在人工智慧的發展中，有另一項被稱為人工生命的分支，目的在於用人工的方法來表現出似生命的行為，最終達到創造人工生命的效果。
本研究取電腦遊戲Spore為例子，以其中的遊戲生物行為作為範本，並配合人工生命方法加以改良，創造一新的遊戲用生物模型。目的為達到更符合自然演化學理依據、更豐富、更似生命的遊戲用生物行為模型。
在研究方法上，本研究配合3D圖像引擎與生物行為模型建立了一個測試程式，並分別建立四項不同的場景來從各種角度測試生物行為模型。接著在得到的數據上，依照遊戲經驗評估、生物行為並與其他研究加以比較。
最終得到的結果為本研究的生物模型大部分皆符合預期，且表現良好，只有少幾項行為需要加以改良。並從四個角度提出了未來的改良方向，分別為強化與增加生物行為、改良基因編碼與生物個體表現的關聯性、加入物理與環境互動、將模型使用於其他引擎或遊戲之上。

The game artificial intelligence (game-AI), plays a more important role in video games. A good game-AI design can make a game performs better and enriches the game. In the related academic AI research, there’s a branch called Artificial Life (AL). The goal of AL is to achieve life-like behavior by artificial means and create artificial life in the end.
This research take the computer game Spore as an example, combines spore’s in-game creature behavior and AL method to create a new creature model for games. The goal of this research are to design a more abundant, life-like creature behavior model for games which conforms to theory of evolution.
In this research, a testing program with 3D graphic engine and creature behavior model is applied. Four different scenes from various aspects are designed to test the proposed model. The heuristic evaluation for playability is measured and the results compared with other researches.
The performance of the proposed model is satisfactory and more creature behaviors, strengthen relation between gene code and creature performance, physical interaction with environments can be gained more efforts in the future study.

目 錄
摘要 i
Abstract iii
目錄 v
表目錄 ix
圖目錄 xi
第一章 緒論 1
第一節 電腦遊戲中的人工智慧 1
第二節 Spore介紹 3
第三節 研究動機與研究目的 5
第二章 文獻探討 7
第一節 人工生命 7
第一小節 人工生命研究中的生物模型 7
第二小節 人工生命研究中的基因編碼 10
第三小節 演化(Evolution)與物競天擇(Natural Selection) 15
第二節 人工智慧 16
第一小節 基因演算法(Genetic Algorithm, GA) 16
第二小節 遊戲人工智慧 – 決策、移動與尋找路徑 17
第三節 遊戲性(Gameplay) 21
第一小節 遊戲性評估 21
第二小節 遊戲中的生物行為 22
第三章 研究方法 25
第一節 模型之生物設計 25
第二節 模型之基因編碼 28
第三節 模型之生物物種 30
第一小節 生產者 30
第二小節 初級消費者 30
第三小節 次級消費者 31
第四節 生物行動模型 33
第五節 模擬場景 36
第一小節 基本場景A 36
第二小節 基本場景B 36
第三小節 基本場景C 36
第四小節 數量測試 37
第四章 結果與分析 39
第一節 基本場景A 39
第二節 基本場景B 45
第三節 基本場景C 52
第四節 數量測試 61
第五節 與其他研究比較 68
第五章 討論與建議 71
第一節 數據分析與討論 71
第一小節 草的生長 71
第二小節 蠕蟲的行動 72
第三小節 甲蟲的行動 73
第四小節 數量測試 75
第五小節 與其他研究比較 76
第六小節 總結 77
第二節 建議與未來發展 78
第一小節 強化與增加生物行為 78
第二小節 改良基因編碼與生物個體表現的關聯性 78
第三小節 加入物理與環境互動 78
第四小節 使用於其他引擎或遊戲之上 79
參考文獻 81
附錄 87

 
 
表 目 錄
表2-13 Spore生物行為整理(來源：整理自Maxis, 2008) 23
表4-1 基本場景A測試前生物基因編碼 39
表4-1（續） 基本場景A測試前生物基因編碼 40
表4-2 基本場景A測試後新增的生物基因編碼 40
表4-2（續） 基本場景A測試後新增的生物基因編碼 41
表4-8 基本場景B測試後的生物基因編碼 45
表4-8（續） 基本場景B測試後的生物基因編碼 46
表4-18基本場景C測試後的生物基因編碼 52
表4-18（續） 基本場景C測試後的生物基因編碼 53
表4-30數量測試執行後的生物基因編碼 61
表4-30（續-1） 數量測試執行後的生物基因編碼 62
表4-30（續-2） 數量測試執行後的生物基因編碼 63
表4-30（續-3） 數量測試執行後的生物基因編碼 64

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