近幾年來，在資訊科技急遽發展之下，資訊產品的功能已不再只是提供單一的功能，而是具備多重的功能，例如手持式電話不單單只是具備傳統式的電話功能，而是一個小型的智慧型電腦系統，有鑑於此一趨勢下，我們的研究是在這些系統中運用多代理人的特性自動達成溝通行為與資訊的傳遞、改進傳統的流程、減少管理成本以及提供更加靈活的資源運用。因此，在本論文中我們提出四種多代理行為，包括合作行為、溝通行為、協調行為及競爭行為，並且說明在多代理人中的溝通以及資源靈活運用策略ARAS(包括Amplification (用戶數量是大的，並且資源可能得到更多) 、Restriction (用戶數量是大的，並且資源不可能得到更多) 、Adjustment (數量是少量的用戶，並且資源是更多)以及Surveillance (用戶數量是少量，並且資源也是較少) )。 此外，我們也使用了多個多代理人系統來說明多代理人行為與資源運用的結果，例如， Intelligent Parking System (IPS) ，IPS是一個整合了現有的RFID技術與多代理人行為，提供一個即時停車場狀態的訊息、 Resource Management System(RMS)，RMS導入了資源管理策略ARAS以及多代理行為，提供一個較靈活的資源管理系統和Mobile Learning Portal (MLP)，MLP是一個創新的互動式系統，包括學習、測試、警示、歷史資訊、社群及個人化。

In recent years, information technology (IT) has rapidly grown in popularity, with IT products beginning to provide more advanced functionality. For example, mobile phones now act not only as conventional phones but also as intelligent computer systems. In this vein, our research seeks to incorporate multi-agent characteristics into such products so that they can automatically execute tasks in the background, transmit messages, improve traditional processes, and reduce management costs, and thus provide more flexibility in the management of resources.  Hence, we propose four types of multi-agent behavior—cooperation, communication, coordination, and competition—to realize a degree of interoperability among agents, as well as an amplification (large user volumes and a significant volume of available resources), restriction (large user volumes and constrained resources), adjustment (low user volumes and a significant volume of available resources), and surveillance (low user volumes and constrained resources), i.e., ARAS, approach to flexible resource management. In addition, we apply the proposed concepts in suggested implementations of various multi-agent behavior systems (case studies): an intelligent parking system (IPS), which integrates existing RFID technology and concepts of multi-agent behavior to provide parking lot information in real time; a resource management system (RMS), which implements the ARAS strategy and concepts of multi-agent behavior to provide a more flexible resource management system; and a mobile learning portal (MLP), which is an innovative, interactive system that includes a number of agents for varying purposes (i.e., learning, testing, alarm, history, community, and personalization).

Chapter 1 Introduction	1
1.1 Background	1
1.2 Motivation	3
1.3 Organization of Thesis	4
Chapter 2 Related Work	5
2.1 Review of the Principles of Agent Technologies	5
2.1.1 General Concept of an Agent	6
2.1.2 Agent Activities and the Interoperability Model	9
2.1.3 Agent Communication Language (ACL)	13
2.2 Telecommunications Billing System	16
2.2.1 Billing Architecture	16
2.2.2 Charging Data for CDRs/EDRs/IPDRs	18
2.3 Android-An Open Handset Alliance Project	19
Chapter 3 Multi-agent Interactions and Collaboration	21
3.1 Multi-agent Synchronous/Asynchronous	21
3.2 Multi-agent behaviors	23
3.2.1 Cooperation Behavior	23
3.2.2 Communication Behavior	25
3.2.3 Coordination Behavior	26
3.2.4 Competition Behavior	27
3.3 Summary	31
Chapter 4 The ARAS Strategy of Multi-agent Systems	33
4.1 ARAS Definition	33
4.1.1 Amplification	35
4.1.2 Restriction	36
4.1.3 Adjustment	37
4.1.4 Surveillance	38
4.2 The ARAS Algorithm for a Multi-agent Strategy	39
4.3 Formal Method of ARAS Strategy Implementation for a Multi-agent System	43
4.4 The Relationship between Agent Behaviors and the ARAS Strategy	51
4.5 Summary	53
Chapter 5 Evaluation and Discussion	55
5.1 The Foundation Emulator Framework	55
5.2 Mobile	58
5.2.1 Family Care System	58
5.2.2 Mobile Learning Portal	65
5.2.3 Intelligent Parking System	72
5.3 Stationary	83
5.3.1 General Communication Procedure	83
5.3.2 Force Interrupt Procedure	84
5.3.3 Communication Agent	85
5.3.4 Monitor Agent	86
5.3.5 Policy Agent	87
5.3.6 System Application	87
5.4 Summary	90
Chapter 6 Conclusions and Future Work	92
REFERENCES	95

Figure 1-1 Thesis Organization	4
Figure 2-1 Agent Announcement State Transition Diagram	10
Figure 2-2 The Abstract model of KQML	13
Figure 2-3 KQML string syntax in BNF	15
Figure 2-4 Billing System	16
Figure 2-5 Android Architecture	19
Figure 3-1 Synchronous Multi-agent System	22
Figure 3-2 Asynchronous Multi-agent System	22
Figure 3-3 Multi-agent behaviors	23
Figure 3-4 Cooperation behavior	23
Figure 3-5 Communication behavior	25
Figure 3-6 Coordination behavior	26
Figure 3-7 Competition behavior	28
Figure 4-1 The resource control cycle	33
Figure 4-2 The strategy quadrant diagram	34
Figure 4-3 The ARAS strategy Communication State Diagram	34
Figure 4-4 Amplification Control Process	35
Figure 4-5 Restriction Control Process	36
Figure 4-6 Adjustment Control Process	37
Figure 4-7 Surveillance Control Process	38
Figure 4-8 The Exploitation Rate Comparison Chart	42
Figure 4-9 The Relationship between Agent Behaviors and the ARAS Strategy	51
Figure 4-10 Call Center with ARAS	54
Figure 5-1 Foundation Emulator Framework	55
Figure 5-2 Family Care System Diagram	58
Figure 5-3 Family Care System Architecture	62
Figure 5-4 FCS communication amongst agents	63
Figure 5-5 Family Care System Implementation Diagram	64
Figure 5-6 MLP system Diagram	65
Figure 5-7 Mobile Learning Portal Agent State Diagram	66
Figure 5-8 Learning Agent State Diagram	67
Figure 5-9 Testing Agent State Diagram	67
Figure 5-10 Alarm Agent State Diagram	68
Figure 5-11 History Agent State Diagram	69
Figure 5-12 Community Agent State Diagram	70
Figure 5-13 Personalization Testing Agent State Diagram	71
Figure 5-14 RFID System Architecture	72
Figure 5-15 Intelligent Parking System Architecture	73
Figure 5-16 Intelligent Parking System	74
Figure 5-17 Authentication Agent State Diagram	75
Figure 5-18 Service Agent State Diagram	77
Figure 5-19 RFID Agent State Diagram	78
Figure 5-20 Billing System Architecture	80
Figure 5-21 Billing Agent State Diagram	80
Figure 5-22 System Architecture of Resource Management System	83
Figure 5-23 General Communication Procedure	84
Figure 5-24 Force Interrupt Procedure	85
Figure 5-25 Communication Agent State Diagram	86
Figure 5-26 Monitor Agent State Diagram	86
Figure 5-27 Policy Agent State Diagram	87
Figure 5-28 Computer Lab RMS system functions and GUI	89

Table 1-1 The evolution of cellular phone networks	1
Table 2-1 Classification of Existing Methodologies	6
Table 2-2 Agent Classifications	10
Table 2-3 Agent Communication Function _Name	11
Table 2-4 Agent Communication Parameter _Name	11
Table 2-5 Agent Communication Action _Type	11
Table 2-6 Agent Communication Message _Type	12
Table 2-7 Summary of reserved performatives, for sender S and recipient R.	14
Table 3-1 Agent Attributes and Class Relationships	21
Table 3-2 Classification of Agent behavior	31
Table 4-1 The Exploitation Rate of Definition 4.1 I	41
Table 4-2 The Exploitation Rate of Definition 4.2 (t=6) II	41
Table 4-3 The Exploitation Rate of Definition 4.2 (t=8) III	42
Table 4-4 The Comparisons of I, II and III Exploitation Rate	42
Table 4-5 The Initial State of ARAS	47
Table 4-6 The Amplification State of ARAS	48
Table 4-7 The Restriction State of ARAS	48
Table 4-8 The Adjustment State of ARAS	49
Table 4-9 The Surveillance State of ARAS	49
Table 4-10 The Return Situation of ARAS	50
Table 5-1 Cross Platform Using Agent	56
Table 5-2 the relationships between roles and modules of the Family Care System	61
Table 5-3 MLP Agent relationships	71
Table 6-1 Agent-based behavior research	93

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