International Journal of Electronic Business Management, Vol. 2, No. 1, pp. 127-137 (2007)
127
A COLLABORIATIVE KNOWLEDGE MANAGEMENT AND REPRESENTING DIFFERENT INDUSTRIAL DESIGN STAKEHOLDERS BY MULTI-AGENTS Ji-Hyun Lee* and Huai-Wei Liu Department of Digital Media Design & Graduate School of Computational Design National Yunlin University of Science Technology Yunlin (640), Taiwan
ABSTRACT Collaboration benefits the process of complex design. However, there are many communication problems among different stakeholders in the domain of industrial design. In addition, the sharing of real-time information and updating information can also pose difficulties. This paper proposes an agent-based collaborative system to support stakeholders to deal with the complex communication problems and information management. The system is composed of both a web-based collaborative system to communicate and share information immediately, and a multi-agent system (MAS) integrated with KW architecture to possess different levels of competence at performing a particular task. The objective is to provide different stakeholders with an effective communication platform to integrate a variety of representational methods of transferring knowledge and the multi-agents that represent different stakeholders to simulate the communication and collaboration in the real world. To demonstrate the proposed concepts, a system prototype has been implemented for notebook design for the company ASUS, a leading notebook manufacturer based in Taiwan. Keywords: Web-based Collaborative System, Computer-Supported Cooperative Work, Multi-agent System, Knowledge Warehouse, Widget Engine
1. INTRODUCTION *
In business and engineering, new product development is the complete process of bringing a new product to market. Because the product development process typically requires both engineering and marketing expertise, cross-functional teams are a common way of organizing projects [21]. There is substantial evidence to support the statement that collaboration represents more than just the sum of the parts. Human–human collaborative problem-solving theory suggests that people construct and maintain an understanding through dialog in which meanings are accrued incrementally, as well as evidence of what has been understood to date [17]. For this reason, collaboration benefits the process of complex design. A development project usually involves diverse team members such as sales manager, project manager, industrial designer, and mechanical, electrical, and layout engineers. Different stakeholders have different views of the system, while they also need to be able to communicate with each other using common models and languages [13]. *
Corresponding author:
[email protected]
According to Burdman [2], however, there are 11 factors that cause poor communications, and Lu and Lee [15] selects 6 factors our of the 11 factors that can be solved by computer supported systems: (1) people have backgrounds in different disciplines; (2) a lack of mutual understanding of terminology; (3) ineffective meetings; (4) proximity; (5) fear; and (6) lack of a good communication structure/system. In addition, the sharing of real-time information and updating information can also pose difficulties. Knowledge management (KM) is a technology that focuses on the knowledge involved in a set of problem situations or in a system [20]. Knowledge warehouse (KW) architecture not only facilitates the capturing and coding of knowledge, but also enhances the retrieval and sharing of knowledge across an organization [16]. Moreover, software agents integrated with KM system have been acknowledged as a promising approach through the metaphor that an agent can act as a personal assistant. The agent acquires its competence by learning from the user as well as from agents assisting other users [18]. This paper, therefore, proposes an agent-based collaborative system to support stakeholders to deal with the complex communication problems and
128
International Journal of Electronic Business Management, Vol. 5, No. 2 (2007)
knowledge management. The system is composed of both a web-based collaborative system to communicate and share information immediately, and a multi-agent system (MAS) integrated with KW architecture to possess different levels of competence at performing a particular task. The objective is to provide different stakeholders with an effective communication platform to integrate a variety of representational methods of transferring knowledge and the multi-agents that represent different stakeholders to simulate the communication and collaboration in the real world. The system especially focuses on the way in which to efficiently communicate between people in the marketing and design sections of an organization, because the sales manager rarely has a chance to communicate with the industrial designers or engineers. In addition, not all requirements can be incorporated in the industrial product because of design and technology constraints. As the project manager is involved for both areas, it is important to consider communication between the project manager and the sales manager, as well as communication between the project manager and the industrial designer or engineer (Figure 1).
system was integrated with computer-supported collaborative work environments (CSCW) technology that enables different stakeholders to communicate with the system and with each other. The system design principles involved in this prototype can be extended to other design domains.
2. BACKGROUND 2.1 New Product Design Development Process in Industrial Design There are several stages in the new product development process (Figure 2).
Figure 2: New product development process
Figure 1: Concept diagram of communication flow for the proposed system A system prototype has been implemented for notebook design for the company ASUS, a leading notebook manufacturer based in Taiwan, to demonstrate the proposed concepts. Understanding the entire notebook development process at ASUS was necessary to develop the system: first, by interviewing different stakeholders domain knowledge and work scenarios was acquired; second, in terms of knowledge management, data from the interviews was analyzed and the data information was stored in different databases as a KW and a decision instance database; third, multi-agent system (MAS) was integrated and used to assist in stakeholders’ collaborative work and in assigning tasks; Finally, in terms of Web-based distributed technology, our
These steps may be iterated as needed. To reduce the time the process takes, many companies are completing several steps at the same time. Most industry leaders see new product development as a proactive process where resources are allocated to identify market changes and seize upon new product opportunities before they occur. Many industry leaders see new product development as an ongoing process in which a new product development team is always looking for opportunities [22]. 2.2 Knowledge Management for Collaborative Systems 2.2.1 Knowledge Management Systems KM focuses on the knowledge components within a system; some knowledge may be explicitly represented (in the form of information databases, policies and procedures, for example) and some may be implicit (in the form of tacit knowledge, organizational culture, habits, etc.). One goal of KM is to facilitate the transformation of implicit knowledge into accessible explicit knowledge that can be brought to bear in relevant problem-solving situations [20]. Knowledge management systems (KMSs) are tools aimed at supporting knowledge management.
J. H. Lee et al.: A Collaboriative Knowledge Management and Representing Different Industrial Design KMSs evolved from information management tools that integrated many aspects of CSCW with information and document management systems [8][10][14]. A KMS provides support for many information functions, including: acquiring and indexing, capturing and archiving; finding and accessing; creating and annotating; combining, collating and modifying; and tracking [6]. These KMS functions allow multiple individuals to organize meaningful activities around shared and reusable artifacts to achieve specific goals. In short, a KMS addresses the distributed nature of work and expertise [19]. KM methods that help to move knowledge include: (1) face-to-face communication methods, e.g. peer assist, lessons learnt reviews, knowledge fairs; (2) computer-based communication methods, e.g. email, Lotus Notes, communities of practice; (3) storage-and-retrieval using computer systems, e.g. intranets, knowledge books; and (4) knowledgeBased Systems, e.g. expert systems. 2.2.2 Knowledge Warehouse The goal of a knowledge warehouse (KW) is to provide the decision maker with an intelligent analysis platform that enhances all phases of the knowledge management process. Two comments can be made to further amplify and explain the KW goal: first, this goal assumes that the user of the KW is the decision maker; second, an intelligent analysis platform is defined as a PC-based platform that makes available to the decision maker an array of analytical tools, each of which utilizes various technologies to aid the socialization, externalization, combination, and internalization of knowledge management [16]. Development and implementation of KW architecture requires the following generic activities [16]: (1) designing and implementing techniques to identify and record both knowledge and ignorance and then designing processes to share, use, and protect such knowledge and to remedy ignorance by learning or knowledge creation; (2) designing and orchestrating contexts, environments, and activities to discover and release what is not formally or explicitly known and possibly coaching and encouraging people to be effective in these processes; (3) articulating and communicating the purpose and nature of knowledge management and connecting it to other strategic and operational initiatives and activities of the organization. These factors are due to the additional tasks that knowledge warehouses should perform. They are the following: (1) Creation of a knowledge management infrastructure. (2) Building a knowledge culture by active promotion of the knowledge agenda, including the development and diffusion of knowledge management models, frameworks, and language. (3) Facilitation of knowledge-oriented
129
connections, coordination and communication throughout, and also without, the organization. 2.2.3 Knowledge Map In addition to the codification of explicit knowledge, some KM authors have proposed methods for categorizing tacit knowledge within the organization. One of the techniques is to create a knowledge map (i.e., a knowledge “Yellow Pages”), which identifies the experts and their field of expertise within the organization. To increase the level of trust in the users of the knowledge map, the inclusion of pictures or videos of the expert has been recommended [4]. In the field of decision-making, knowledge map is a method designed not only to elicit information complexity that the decision makers faced, but also to combine the probabilities associated with each factor to obtain a final probability [1]. Figure 3 shows an example of knowledge management map.
Figure 3: An example of knowledge management map [5] 2.3 Decision Making Process in CSCW based on Multi-Agent Systems Computer Supported Cooperative Work (CSCW) technology must to conform to group work. Agents, especially Multi-Agent System (MAS) can apply CSCW include several reasons as follows: firstly, human is a basic unit for cooperative work in reality society, so CSCW system is an abstract activity to simulate group cooperative work. The autonomous agent very similar human being, to constitute CSCW system has naturalized and necessity. To develop CSCW system need request every member’s behavior to possess intelligence, organization and adaptation, so autonomous agent contains these requirements in CSCW system. Secondly, the agents’ communication behaviors are the same as group members to communicate with each other. The relationship of multi-agent system are equality and collaborative, to emphasize cooperative work must via communication behavior. Therefore, agent can reflect group cooperative work, architecture of organization and communication characteristic [3].
130
International Journal of Electronic Business Management, Vol. 5, No. 2 (2007)
A CSCW system based on agent is defining several agents have cooperative relationship and same goal. According to principle of agent definition, it used a substantiation group of four units’ description: agents, goals, knowledge base, relations [3]. Agents: agent collections, every agent to have problem solving capability. Goals: goal collections, to describe which cooperative work necessary to complete. Knowledge Base: agent’s knowledge base, to describe which knowledge is necessary when to complete cooperative work. Relations: relation collections, to describe relationship between agent and cooperative work.
(2) there is not necessary a global system control, (3) data and knowledge for solving the problem are decentralized, and (4) computations carried out among the agent are asynchronous [7]. Agents in the MAS are distributed geographically, are autonomous but interdependent in their task environments, are embedded with self organization capability, and are adaptive to changes in their environment. For dynamic multi-agent systems, agents need to know how and where to find the other agents. The dynamic nature of agent distribution motivates this research to look at the topological models of MAS and study how these models facilitate or hurdle the agent collaborations [9].
Table 1 Shows the list of agent classifications. Table 1: Agent classifications Property
Other Names
Reactive
(Sensing and acting)
Autonomous
Goal-oriented
Pro-active purposeful
Temporally continuous Communicative
Socially able
Learning
Adaptive
Mobile
Flexible
Character
Meaning Responds in a timely fashion to changes in the environment Exercises control over its own actions Does not simply act in response to the environment Is a continuously running process Communicates with other agents, perhaps including people Changes its behavior based on its previous experience Able to transport itself from one machine to another Actions are not scripted Believable “personality” and emotional state.
One of Multi-agent information systems research goals is to study how an agent adjusts knowledge, goals, skill and plan, to generate the collective behaviors through the interactions among agents. Multi-agent systems are composed of two or more intelligent agents (Figure 4 (a)). An agent has detectors, effecters and a decision-making mechanism (Figure 4 (b)) [23]. A general understanding of MAS is that: (1) each agent has a partial capability to solve a problem,
Figure 4: Multi-agent system [23] To implement Multi-Agent based on CSCW system must solve one basic problem: how to represent an agent. In computer engineering point of view, five units’ description can be represented [3]: N: the name or identification of agent must be one and only and be able to describe agent’s type. I: the interface definition of agent to represent human-computer interaction and communication port (include communication protocol and I/O port). The principle is must to separate agent into interface and functionality. S: the status of agent to describe the internal part of agent’s status, in fact the agent’s behaviors are one process of status and status exchange. T: the matter collections of agent to define agent’s behavior, to represent agent’s functionality and include reasoning capability. K: the knowledge collections of agent to describe necessary knowledge, data, reasoning principle and relation resource for agent’s behavior. Using data structure, database and knowledge base to represent.
J. H. Lee et al.: A Collaboriative Knowledge Management and Representing Different Industrial Design Leading organizations generally hold project managers accountable for meeting cost, schedule, and performance goals. Most project managers have to do several sequences of decision makings: intelligence, design, choice and implementation [11]. Decision Support Systems (DSS) are defined as interactive computer-based systems intended to help decision makers utilize data and models in order to identify and solve problems and make decisions. The DSS concept presumes that the problem pertinent data and models have been created and made available to the system prior to user processing [12]. DSS are further classified into four main categories: data, model, process and communication oriented. Decision making support has evolved over time and across disciplines. Initial support was offered by a DSS, with the typical architecture shown in Figure 3. In the typical DSS, the problem-pertinent data and models are captured and stored as inputs in the system [11]. Figure 5 shows the typical DSS architecture in a system.
131
situation? (6) If have one system can support you in collaboration design, which functionality you need?
Figure 6: Flowchart of the research methodology
Figure 5: Typical DSS architecture [11]
3. METHODOLOGY Figure 6 shows the flowchart of the research methodology. The detailed descriptions are followed. 3.1 Interview with ASUS Staffs The research chose one notebook development process within ASUS for which to collect qualitative data by interviewing different stakeholders such as the manger, designer, and engineer. The questions in the questionnaire are as follows: (1) Which stakeholder are you in whole notebook design process? (2) Please to describe your task scenario and responsibility. (3) Which domain knowledge you have? (4) Which communication problem you have met in collaboration design phase? (5) How to solve communication problem in current
Figure 7: Results of interview Figure 7 is the summarized results of the interview. Within ASUS, the process flow for notebook development is as follows. First, the sales manager is provided with requirements determined from marketing analysis and consumer needs, and then communicates with the project manager. Secondly, on the basis of this information, the project manager decides upon goals, the process schedule, team members for the development, and the sourcing of resources. Thirdly, the industrial designer receives information related to the development goals and draws a 2D graphic that is sent to the mechanical engineer who constructs a 3D graphic and model.
132
International Journal of Electronic Business Management, Vol. 5, No. 2 (2007)
Finally, the electrical engineer designs the connector and electronic components and has the layout engineer design the circuit. Over the entire development process, the engineers largely follow the designer’s idea because the technology exists to support any new type of notebook development. 3.2 Establishment Web-Based Knowledge Management System and Widget Tool This step is to establish knowledge management system and web pages as user interfaces. Widget tools are developed to help user control system easily, check current data immediately and avoid unnecessary information. A widget is a portable chunk of code that can be installed and executed within any separate HTML-based web page by an end user without requiring additional compilation. They are akin to plug-ins or extensions in desktop applications [22]. Figure 8 shows the web-based knowledge management platform.
Figure 9: Knowledge map for ASUS Company
Figure 8: Web-based knowledge management system 3.3 Knowledge Representation (Knowledge Map) On the basis of the information, knowledge map (Figure 9) is made to visualize the context descriptions, and represent and share the knowledge of the whole different stakeholders in a platform. The KM need to define important core process and knowledge resource related to each stakeholder. Using knowledge map (KM) is a good way to display knowledge relationship and understand information easily. Figure 9 clearly shows the knowledge resource, concept and stakeholders’ location. The upright equilateral triangle has three stakeholders as project manager, sales manager and industrial designer. They are first section in design phase. The opposite equilateral triangle has other stakeholders as mechanism engineer, electrical engineer and layout engineer. They are second section in implementation phase. The center location shows the knowledge representation such as 2D or 3D images, descriptions and instances as Figure 10.
Figure 10: Knowledge representation examples 3.4 Establishment the Knowledge Warehouse As each stakeholder owns a different domain of knowledge, a KW that enables stakeholders to store and retrieve their knowledge is established. The project manager uses the KW to make decisions and communicate. Figure 11 shows the location of KW in our particular system. The knowledge related to sales manager is marketing analysis, customer psychology, production cost, etc. For industrial designer, it is design principles, idea generation and drawing representations. The knowledge related to engineer is product mechanics, electrical layout, etc.
J. H. Lee et al.: A Collaboriative Knowledge Management and Representing Different Industrial Design Those are stored in KW as their domain knowledge using images and descriptions. The KW also stores in the agents’ knowledge-base (KB) file. The KB file of each stakeholder represented its domain knowledge is downloadable to the corresponding agent when communication phase. For the decision instances, the project manager's requirements and the decision principles of ASUS are considered and from the decision-making process, necessary information and instances are stored.
2.
133
and assigns work to different agents. It can decide which functionality the stakeholder need and give the correct feedback. Knowledge warehouse agent: the knowledge warehouse agent is linked to the management knowledge warehouse. Each stakeholder can store and share knowledge information via this agent to knowledge warehouse database. And it also can provide decision cases and suggestions for the project manager.
Personal assistant agent: the personal assistant agent can help stakeholder communicate with others or the core system via the collaboration of agents. The stakeholder can download different domain knowledge from knowledge warehouse and conversation with agent use the text like talk to real human. The following two figures are the different agents’ definitions (Figure 12) and framework (Figure 13).
Figure 11 The location of knowledge warehouse Here are the decision-making history and marketing analysis information for the project manager to add to knowledge warehouse and thereby help in making important decisions. The project manager must consider the following tasks over the entire notebook development process: 1. Using marketing analysis data to formulate the notebook development goal and design target. 2. Deciding upon which stakeholders to organize into the development team, assigning tasks, and communication with stakeholders. 3. Arranging and maintaining the development schedule. 4. Choosing references and collecting resources and supplies for the industrial designer. 3.5 Establishment Different Role in Multi-Agent System Based on CSCW The stakeholder can communicate with others or the core system via the collaboration of agents in multi-agent system (MAS). Two types of agents are established by different viewpoints: 1. Work center agent: the work center agent include several sub-agents as follows: Interface agent: the interface agent provides an interface as interaction communication platform for stakeholders and according to user’s operation sends requirement messages to the Task agent. Task agent: the task agent operates according to the requirement messenger
Figure 12: The agents’ definition in system The two different types of agents are integrated by using communication channel to be a whole multi-agent system. It supports the knowledge management platform to let stakeholder operate knowledge management system and communicate with agents. The multi-agent system framework is shown in Figure 13.
Figure 14: Multi-agent system framework
134
International Journal of Electronic Business Management, Vol. 5, No. 2 (2007)
4. PROTOTYPE IMPLEMENTATION 4.1 System Architecture Figure 15 shows the architecture of the system. It provides a knowledge management platform to store and share information. All information is stored in a central database (KW) and communicated by MAS environment. The system also provides the data upon which the project manager makes decisions.
Figure 15: The system architecture 4.2 System Development Environment 1. Graphical User Interface (GUI): The system development environment in this research uses LifeType OpenSource Blogging Platform and PHP as a web-based development language, because PHP is a general-purpose programming language with a number of features that make the language well-suited for use on the World Wide Web. The LifeType API provides an abstraction layer to represent all entities that are used: articles, users, blogs, etc. 2. Knowledge Warehouse (KW) database: The knowledge warehouse database uses MySql to support knowledge management platform. 3. Multi-Agent System (MAS): Work center agent part uses JADE (Java Agent DEvelopment Framework) Framework, fully implemented in Java language, and JADE makes the implementation of multi-agent systems simple. Personal assistant agent part uses Verbot-agent (Verbal-Robot), a commercial software to develop agents. The Verbot is a popular chatterbot program and artificial intelligence (AI) Software Development Kit (SDK) for the Windows platform and for the web [20]. The Verbot-agent development platform provides a knowledge- base development environment “Verbot Editor” and uses the knowledge-base template to create rules, CSV data driven knowledge-bases.
4.
Widget tool: The Widget Engine is a JavaScript runtime engine for Windows. What sets Widget Engine apart from other scripting applications is that it takes full advantage of today's advanced graphics. JavaScript and Notepad++ are used to implement widget tool.
4.3 Scenarios for Notebook Design Process in Company ASUS Roles: Project manager – Max Liu Industrial Designer – Lisa Lee Mechanical Engineer – John Wu Electrical Engineer – Jerry Kim Layout Engineer –Nicolas Chung Project manager in ASUS, Max Liu has got the new notebook design task today. He already finished the discussions with Sales manager in meeting and clearly knew the design target for this time. Then, he chose Lisa, John, Jerry and Nicolas to be the team members. Whole notebook design process will be started. Max logins the system, writes down necessary information and updates to the system. The system will publish the information on KM communication platform (Figure 16).
Figure 16: An example of Max’s descriptions Then, other team members can see the latest information from widget tool (Figure 17).
Figure 17: Widget tool to display latest information When Lisa finishes the sketches of a notebook, she submits to communication platform supporting 2D image and the descriptions.
J. H. Lee et al.: A Collaboriative Knowledge Management and Representing Different Industrial Design
Figure 18: 2D sketches and the descriptions for industrial designer Max checks the sketches and descriptions from Lisa and discusses with Sales manager about the detailed design part. After Max gives Lisa the new concept to redesign the part of the notebook and he also wants Lisa to make sure the current main-board size can compatible with her design. The problem belongs to John, mechanical engineer, but he is not in his office now. Lisa, therefore, uses Verbot-agent to load knowledge-base file related to the mechanical engineering domain from knowledge warehouse. She communicates with Verbot-agent and successfully gets the result (Figure 19).
135
Figure 20: Lisa publishes the second version John have got informed that the notebook shape design has already finished so that he downloads the 2D images from the KM communication platform albums page (Figure 21).
Figure 21: John downloads the 2D images from the KM albums page John, Jerry and Nicolas communicates a lot and continues to improve the notebook model, location of connector, electronic components and circuits (Figure 22, 23, 24). Max needs to check everything on schedule and to know every stakeholder’s requirements and problems, and gives appropriate feedback using KM communication system.
Figure 19 Lisa communicates with Verbot-agent When Lisa finishes the second version of the notebook sketches, she submits them again (Figure 20). Max checks the second version and feel good, so he wants Lisa send those images to John and let John built 3D model and arrange notebook components and connectors based on the sketches.
Figure 22: 3D model for notebook design created by John
136
International Journal of Electronic Business Management, Vol. 5, No. 2 (2007)
Figure 23: Electronic components created by Jerry and communication with John and Nicolas
Our proposed concept can solve several communication problems in product development process via improved communication, collaboration and distribution of multiple information sets to each of the stakeholders within the design team. There are several directions the system can be extended in the future: 1. Support for multi-file formats: different domain stakeholders may use different software to finish each part of the process, thus producing a variety of file formats. If the proposed system can be adapted to accept different file formats, this will help make communication more convenient and enhance the sharing of information. 2. Record data within the server: If the stakeholders are agreeable, the system can record their work behavior. In this way, I can acquire considerable data concerning cooperative work; such data is useful for research into collaboration design in academia and business.
REFERENCES Figure 24: Nicolas publishes the circuit diagram for notebook and Max gives comments Max really likes the widget tools because he can always update the latest news and check contents by them (Figure 25). Now, since everything is done, Max sends the final prototype and necessary information to product factory to prepare the production. And sales manger will prepare an advertisement to sell this new type of notebook.
1.
2.
3.
4.
5.
Figure 25: A widget tool to display latest information
6.
5. CONCLUSION The paper developed a prototype system that can support communication and the sharing information among different stakeholders by using a multi-agent system to represent different stakeholders. The system also can provide data for the project manager to analyze, consider, and decide upon over the entire development process. The Verbot-agent system and widget tool can link information updating to platform immediately.
7.
8.
Browne, G., Curley, S. and Benson, P., 1997, “Evoking information in probability assessment: Knowledge map and reasoningbased directed questions,” Managements Science, Vol. 43, No. 1, pp. 1-14. Burdman, J., 1999, Collaborative Web Development: Sstrategies and Best Practices for Web Teams, Addison Wesley Professional Press. Chen, N. and Su, D., 2000, “Agent-based CSCW system and communication implementation,” Journal of Guangxi University, Vol. 25, No. 2, pp. 94-97. Davenport, T. and Prusak, L., 1998, Working Knowledge: How Organizations Manage What They Know, Harvard Business School Press. Donald, C., 2004, A Brief History of Information and Knowledge, http://www.nwlink.com/~donclark/history_kno wledge/knowledgehistory.html. Edmonds, G. and Pusch, R., 2002, “Creating shared knowledge: Instructional knowledge management systems,” Educational Technology & Society, Vol. 5, No. 1, http://ifets.ieee.org/periodical/vol_1_2002/. Roberto, A. F. M., 1999, “Towards a standardization of multi-agent system frameworks,” Journal of the Association for Computing Machinery, Vol. 5, No. 4, http://www.acm.org/crossroads/xrds5-4/multiag ent.html. Ganesan, R., Edmonds, G. and Spector, J., 2001, “The changing nature of instructional design for networked learning,” Networked Learning in
J. H. Lee et al.: A Collaboriative Knowledge Management and Representing Different Industrial Design
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
Higher Education, pp. 93-109. Giampapa, J., Paolucci, M. and Sycara, K., 2000, “Agent interoperation across multi agent system boundaries,” Proceedings of the Fourth International Conference on Autonomous Agents, pp. 179-186. Greif, I., 1988, Computer-supported Cooperative Work: A Book of Readings, Morgan Kaufmann Press. Guisseppi, A. F., 2002, “An architecture for the integration of decision making support functionalities,” Decision Making Support Systems: Achievements, Trends and Challenges For, pp. 1-19. Hooghiemstra, J. S., Kroon, L. G., Odijk, M. A., Salomon, M. and Zwaneveld, P. J., 1999, “Decision support systems support the search for win-win solutions in railway network design,” Interfaces, Vol. 29, No. 2, pp. 15-32. Johannesson, P. and Perjons, E., 2001, “Design principles for process modeling in enterprise applications integration,” Information Systems, Vol. 26, No. 3, pp. 165-184. Kling, R., 1991, “Cooperation, coordination and control in computer-supported work,” Communications of the ACM, Vol. 34, No. 12, pp. 83-88. Lu, K. H. and Lee, J. H., 2005, “Web modeling for improving communication in web designers and programmers,” Proceedings of the 12th ISPE International Conference on Next Generation Concurrent Engineering, pp. 267-276. Nemati, H., Steiger, D., Iyer, L. and Herschel, R., 2002, “Knowledge warehouse: An architectural integration of knowledge management, decision support, data mining and data warehousing,” Decision Support Systems, Vol. 33, No. 2,pp. 143-161. Ostwald, J., 1995, “Supporting collaborative design with representations for mutual understanding,” Proceedings of CHI ’95, http://www.sigchi.org/chi95/proceedings/doctor al/jod_bdy.htm. Pattie, M., 1994, “Agents that reduce work and information overload,” Communications of the
19.
20.
21.
22. 23.
137
ACM, Vol. 37, No. 7, pp. 30-40. Salomon, G., 1993, Distributed Cognitions: Psychological and Educational Considerations, Cambridge University Press. Spector, J. and Edmonds, G., 2002, “Knowledge management in instructional Design,” ERIC Digest, http://www.ibstpi.org/downloads/Spector-edmo nds-km-id.pdf. Wikipedia, 2006, New Product Development, http://en.wikipedia.org/wiki/New_product_deve lopment. Wikipedia, 2006, Widget Engine, http://en.wikipedia.org/wiki/Widget_engine. Yamada, K., Nakakoji, K. and Ueda, K., 2004, “A multi-agent systems approach to analyze online community activities,” Proceedings of the 4th International Conference on the Advanced Mechatronics: Toward Evolutionary Fusion of IT and Mechatronics, pp. 595-600.
ABOUT THE AUTHORS Ji-Hyun Lee is an Assistant Professor in the Department of Computational Design at National Yunlin University of Science &Technology (NYUST), Taiwan R.O.C. She received her Ph.D. degree in Computational Design at Carnegie Mellon University in 2002, USA. Her current research and teaching interests are in the general area of Computational Design. In particular, she is interested in Case Base Reasoning, Rule Base System, Expert System and Computer Aided Design (CAD). Huai-Wei Liu is a Master graduate student of Computational Design at National Yunlin University of Science &Technology (NYUST). His research interests are Collaborative Design, Knowledge Base System and Multi-Agents System. (Received May 2006, revised November 2006, accepted April 2007)
