電子化協商的發展方興未艾，各種協商支援系統也紛紛被提出。在眾多的支援項目中，最受人矚目的莫過於對手喜好預測。若能了解對手喜好，便有機會主導協商流程，達成預設目標。學者們雖然提出了許多對手喜好預測方法，但多以精準預測為目標，鮮少考慮當了解對手喜好之後，己方該以何種策略來因應，使預測的積極效果大打折扣。有鑑於此，本研究致力發展一套具有動態策略調整能力的對手喜好預測方法，其能根據預測結果，在協商中導引雙方的出價過程，取得預設的協商結果。為達成此目的，我們首先以Faratin提出的協商模型為基礎，配合基因演算法，預測對手可能的喜好。為了描述協商者的態度，我們設計了多種目標函數，以引導協商流程的進行。當進行動態策略調整時，我們則以預測結果為基礎，透過內部模擬協商，找出可行的策略調整方式，以符合目標式的規範。為驗證方法的有效性，本研究進行了大量的模擬實驗。實驗結果顯示:有預測的一方，無論協商者選擇何種策略目標，均能提升己方的效用值。當雙方均使用喜好預測，且均以自利（selfish）為目標時，可得到最佳的效用總合。若選擇互利或慷慨為遠程目標，則可降低協商回合數，並提高協商成功率。當配合動態策略調整，則效果可獲得進一步提升，顯示動態策略調整的必要性與有效性。

The development of E-Negotiation is still growing as various Negotiation Supporting Systems are also being offered one after another. Among various Supporting Systems, nothing is getting more attention than opponent’s preferences predictions. If we understand opponent’s preferences, we can get the chance to lead the negotiation process and achieve the preset goal. Though scholars have offered many methods to predict opponent’s preferences, most of them focus on accuracy, rather than knowing what tactics to respond one understood their preferences which end up reducing the effects of predictions. In regard to this fact, this research dedicates to develop opponent’s preference prediction which have the ability of dynamic tactics, it can attain the predicted negotiation outcome. In order to attain this goal. First, we use the negotiation model which put forward by Faratin as base, working in coordination which Genetic algorithm to predict possible opponent’s preference. To describe negotiation’s attitude, we design several object function to guide the process of negotiation. When doing the adjustment of dynamic tactics, we find out practicable method of tactic adjustment by simulative negotiation inside on the basis of predictive result to confirm with objective standard. To testing the validity of the method, this research has proceeded abundant of simulated experiments. The result of the research shows that no matter what kind of tactics’ goal the negotiation have chosen , they can an upgrade their own utility value in the side which has doing prediction. When both sides use opponent’s preferences prediction and also make selfish as their goal, it can get the best combination of utility. If we choose mutually beneficial or generosity as the long-term object, we can reduce the rounds of negotiation and raise the rate of success at the same time. The effect can obtain further promotion when matching up dynamic tactics. Then, it reveals the necessity and validity in adjustment of dynamic tactics.

目錄
第一章 緒論	1
第二章 相關理論與技術	6
2.1協商類型	6
2.2協商模型	7
2.3協商戰略與策略	9
2.4基因演算法	11
第三章 對手喜好預測	13
3.1對手喜好預測之重要性	13
3.2對手喜好預測之方法	15
3.3使用基因演算法進行對手喜好預測	18
第四章 了解對手喜好狀況下之策略調整	20
4.1預測提案表與候選提案集	20
I. 預測提案表	20
II. 候選提案集	22
4.2 協商目標的設定	23
4.2.1 以效用值為主之策略目標	23
4.2.2 以回合數與成功率為主之策略目標	26
4.3己方策略動態調整	28
4.4 考量對手喜好預測與動態策略調整之協商流程	30
第五章 實驗與結果分析	32
5.1實驗設計與評量指標	32
5.2 實驗結果	34
5.2.1對手喜好預測之準確度	35
5.2.2對手喜好預測之效能（以效用值為目標）	37
5.2.3 對手喜好預測之效能: 以回合數與成交率為考量	40
5.2.4策略動態調整之效能驗證	41
5.2.5 對手喜好變動之效能驗證	42
5.2.6對手喜好變動與策略動態調整之效能驗證	45
5.2.7雙方都具有預測能力	47
5.2.8雙方具有預測能力且喜好變動與策略動態調整	50
第六章 結論與未來研究	53
參考文獻	55
附錄：協商實驗結果	58

表目錄
表 3  1：對手喜好預測參數	17
表 3  2：對手喜好預測之基因編碼	18
表 3  3：基因編碼長度	19
表 4  1：預測提案表	21
表 4  2：以效用值為主之策略目標	25
表 4  3：不同策略與假想對手協商之協商結果	29
表 5  1：實驗相關參數	33
表 5  2：雙方皆無預測對手喜好之協商結果（整合式協商）	37
表 5  3：雙方皆無預測對手喜好之協商結果（分配式協商）	37
表 5  4：我方預測對手喜好之協商結果（整合式協商）	39
表 5  5：我方預測對手喜好之協商結果（分配式協商）	39
表 5  6：以效用值為主之策略（整合式協商）	40
表 5  7：以雙方關係為主之策略（整合式協商）	41
表 5  8：無策略動態調整之協商結果（分配式協商）	42
表 5  9：策略動態調整之協商結果（分配式協商）	42
表 5  10：雙方皆無預測之對手喜好改變（分配式變整合式）	44
表 5  11：我方預測對手之對手喜好改變（分配式變整合式）	44
表 5  12：雙方皆無預測之對手喜好改變（整合式變分配式）	45
表 5  13：我方預測對手之對手喜好改變（整合式變分配式）	45
表 5  14：對手喜好變動（分配式變整合式）	46
表 5  15：對手喜好變動與策略動態調整（分配式變整合式）	46
表 5  16：雙方皆預測對手喜好之分配式協商結果（效用值）	47
表 5  17：雙方皆預測對手喜好之分配式協商（雙方效用和）	48
表 5  18：雙方皆預測對手喜好之分配式協商（雙方效用差）	48
表 5  19：雙方皆預測對手喜好之分配式協商（協商回合數）	48
表 5  20：雙方皆預測對手喜好之分配式協商（協商成交數）	49
表 5  21：雙方皆預測對手之分配式協商（均等效率距離）	49
表 5  22：雙方皆無預測之對手喜好改變（分配式變整合式）	50
表 5  23：雙方皆預測對手且喜好變動與策略動態調整（效用值）	51
表 5  24：雙方皆預測對手且喜好變動與策略動態調整（效用和）	51
表 5  25：雙方皆預測對手且喜好變動與策略動態調整（效用差）	51
表 5  26：雙方皆預測對手且喜好變動與策略動態調整（回合數）	52
表 5  27：雙方皆預測對手且喜好變動與策略動態調整（成交數）	52
表5 28：雙方皆預測對手且喜好變動與策略動態調整（均等效率距離）	52

圖目錄
圖 2  1：基因演算法流程圖	12
圖 3  1：協商動線圖	14
圖 3  2：對手喜好預測挑選方法	16
圖 4  1：協商空間圖	26
圖 4  2：協商空間圖	27
圖 4  3：考量對手喜好預測與動態策略調整之協商流程	31
圖 5  1：實際對手與預測對手效用序列I	36
圖 5  2：實際對手與預測對手效用序列II	36
圖 5  3：對手喜好變動時機	43

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