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記錄 7507 編號 狀態 NC095FJU00392028 助教 建檔完成 查核 索書 查核完成 號 學校 輔仁大學 名稱 系所 資訊工程學系 名稱 舊系 所名 稱 學號 494516287 研究 生(中 簡清榮 ) 研究 生(英 Chien Ching Jung ) 論文 名稱( 應用基因型案例式推論於代理人計畫演化 中) 論文 名稱( Agent Plan Evolution using Genetic Case-based Reasoning 英) 其他 題名 指導 教授( 許見章 郭忠義 中) 指導 教授( Hsu Chien Chang Kuo Jong Yih 英) 校內 不公開 全文 開放 日期 校外 全文 不公開 開放 日期 全文 不開 放理 由 電子 全文 同意 送交 國圖. 國圖 全文 2007.07.17 開放 日期. 檔案 電子全文 說明 電子 01 全文 學位 碩士 類別 畢業 學年 95 度 出版 年 語文 中文 別 關鍵 字(中 代理人計畫演化 BDI模型 案例式推論 基因演算法 ) 關鍵 字(英 Agent Plan Evolution BDI Model Case-based Reasoning Genetic Algorithm ) 本篇論文針對代理人演化提出一個可記憶性的代理人計畫演化模型,以BDI模型 簡單且強大的行為表示為基礎,使用信念、願望及意圖表示代理人的心智狀態, 導入案例資料結構,使代理人擁有記憶能力。代理人計畫結合策略計畫與案例式 摘要( 推論計畫,使代理人擁有策略計畫的能力與參考過去經驗計畫的能力。進階地, 中) 案例式推論計畫中,加入基因演化的概念,利用基因演算法的概念演化代理人的 計畫及調適案例記憶。本論文應用於逃避追蹤者遊戲,遊戲中包含追蹤者、逃避 者及障礙物,並且實作追蹤者代理人說明我們的方法。 This paper addresses an agent plan evolution model, it based on BDI-model which has easy so powerful behavior representation. BDI-model uses belief, desire, and intension to represent agent’s mental state. Leading in case–based data structure make agents have memory ability. Agent plan evolution process combines strategy plan and case-based 摘要( inference plan make agent have the ability of strategy planning and the ability of 英) reference past experience plan. In advance, adding genetic evolution concepts into casebased inference plan, using the concept of genetic algorithm to evolutes agent’s plan and adapt case memory. This paper applied on pursuit-evasion game, which includes pursuers, evaders, and barriers. At last, we propose pursuer agents to describe our approach. 1. 緒論 5 1.1 研究背景與動機 5 1.2 研究目的 6 1.3 研究流程 6 1.4 論文架構 7 2 文 獻探討 8 2.1 BDI代理人模型(BDI Agent Model) 8 2.2 代理人計畫演化 9 2.3 基因演 算法(Genetic Algorithm) 10 2.4 案例式推論(Case-based Reasoning) 12 2.4.1 最鄰近 演算法 13 2.5 CBR-BDI代理人架構 14 2.6 基因型案例式推論(Genetic Case-based Reasoning) 14 3 代理人行動計畫演化方法 16 3.1 知識表示 18 3.2 計劃演化程序 論文 (Plan Evolution Process) 20 4 案例研究 24 4.1 逃避追蹤者遊戲 25 4.2 逃避追蹤者問 目次 題正規化 26 4.3 追蹤代理人知識表示 27 4.3.1 追蹤者代理人的心智狀態 27 4.3.2 案 例表示 30 4.3.3 追逐策略 32 4.4 追蹤代理人計畫流程 35 4.4.1 案例擷取 35 4.4.2 案 例交配 38 4.4.3 案例突變 38 5 系統設計 39 5.1 追蹤者代理人的系統架構 39 5.2 系 統環境 41 5.2.1 硬體規格及設定 41 5.2.2 軟體規格及設定 41 5.2.3 作業環境 41 5.3 系統實作 42 5.4 實驗結果 44 5.4 實驗討論 45 6 結論 47 [1] J. Holland, “Outline for a Logical Theory of Adaptive Systems”, Journal ACM, Vol. 3, pp. 297-314, 1962. [2] J. Holland, “Adaptation in Natural and Artificial Systems”, Ann Arbor,MI: University of Michigan Press, 1975. [3] D. E. 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Lee, “A Multi-Agent Framework for Meeting Scheduling Using Fuzzy Constraints”, Proceedings of the 4th International Conference on Multi-Agent Systems, pp. 409-410, 2000. 論文 53 頁數 附註 全文 點閱 次數 資料 建置 2011/4/18 時間 轉檔 日期 全文 檔存 030540 2011.4.18 10:10 140.136.208.244 new 01 取記 錄 異動 M admin Y2008.M7.D3 23:18 61.59.161.35 M 030540 Y2011.M4.D18 10:10 記錄 140.136.208.244 M 030540 Y2011.M4.D18 10:10 140.136.208.244