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DYNAMIC MULTI-AGENT BASED VARIETY FORMATION AND STEERING IN MASS CUSTOMIZATION riety steering. Based on the decision theory’s model for rational agents, we formally define the function that an agent strives to optimize. The negotiation process between the intelligent agents is based on the target costing concept and a Dutch auction. This is also described in a formal way defining the possible functions which have to be determined. Because we intend to carry out simulations of the entire system, several functions which determine the intelligence of the defined agents should be tested. Based on these simulations we will decide which implementation will lead to a working prototype. Furthermore, a technical architecture for the agentbased variety formation and steering in mass customization is proposed. The main advantages of the developed approach are the easy maintenance of the system, the dynamic variety generation and variety steering, as well as the application of a market mechanism concept supported by agent technology. The adopted market mechanism presents a relevant approach enabling one to overcome the shortcomings of existing interaction systems and variety steering methods. Thus, instead of building rigid rules in the interaction system that map customer requirements into product attributes, the proposed market mechanism approach lets the intelligent agents themselves decide according to the current situation about their suitability to fulfill real customers’ requirements. Furthermore, the market mechanism enables us to connect two relevant concepts in mass customization, namely which product variants should be retained in the product assortment and which specific ones from this assortment should be selected and offered to a particular customer. REFERENCES Blecker, T., Abdelkafi, N., Kaluza, B., and Friedrich, G., 2003. Key Metrics System for Variety Steering in Mass Customization. In MCPC’03, 2 nd Interdisciplinary World Congress on Mass Customization and Personalization, Munich, October 6-8, 2003. Blecker, T., Abdelkafi, N., Kreutler, G., and Friedrich, G., 2004. An Advisory System for Customers’ Objective Needs Elicitation in Mass Customization. In 4th Workshop on Information Systems for Mass Customization, Madeira Island, February 29-March 3, 2004. Ericsson, A., and Erixon, G., 1999. Controlling Design Variants: Modular Product Platforms, Society of Manufacturing Engineers. Dearborn, Michigan. 125 Iyenger, S. S., and Lepper, M. R., 2000. When Choice is Demotivating: Can One Desire Too Much of a Good Thing?, URL: http://www.columbia.edu/~ss957/ publications.html (Retrieval 10. Oct. 2003). Kauffman, S. A., 1993. The Origins of Order: Self-Organization and Selection in Evolution, Oxford University Press, New York. Lingnau, V., 1994. Variantenmanagement: Produktionsplanung im Rahmen einer Produktdifferenzierungsstrategie, Erich Schmidt Verlag GmbH & Co. Berlin. Piller, F. T., 2001. Mass Customization: Ein wettbewerbsstrategisches Konzept im Informationszeitalter, Gabler Verlag. Wiesbaden, 2nd edition. Piller, F. T., and Waringer, D., 1999. Modularisierung in der Automobilindustrie – neue Formen und Prinzipien, Shaker Verlag. Aachen. Pine II, J., 1993. Mass Customization: The New <strong>Front</strong>ier in Business Competition, Harvard Business School Press. Boston. Rathnow, P. J., 1993. Integriertes Variantenmanagement: Bestimmung, Realisierung und Sicherung der optimalen Produktvielfalt, Vandenhoeck und Ruprecht. Goettingen. Rautenstrauch, C., Taggermann, H., and Turowski, K., 2002. Manufacturing Planning and Control Content Management in Virtual Enterprises Pursuing Mass Customization. In Rautenstrauch, C., Seelmann-Eggebert, R., and Turowski, K. (Eds.). Moving into Mass Customization: Information Systems and Management Principles, Springer-Verlag. Berlin Heidelberg, pp. 103-118. Rosenberg, O., 1997. Kostensenkung durch Komplexitaetsmanagement. In Franz, K.-P., and Kajueter, P. (Eds.). Kostenmanagement: Wertsteigerung durch systematische Kostensenkung, Schaeffer Poeschel Verlag. Stuttgart, pp. 225-245. Russel, S., and Norvig, P., 1995. Artificial Intelligence: A Modern Approach, Prentice-Hall, Inc. New Jersey. Schwartz, B., 2000. Self-Determination: The Tyranny of Freedom, URL: http://www.swarthmore.edu/SocSci/ bschwar1/self-determination.pdf Seidenschwarz, W., 2001. Target Costing. Marktorientiertes Zielkostenmanagement, Vahlen. Muenchen, 2 nd edition. Shehory, O., and Kraus, S., 1995. Coalition formation among autonomous agents: Strategies and complexity. In Castelfranchi, C., and Muller, J. P., (Eds.). From Reaction to Cognition, Springer Verlag. pp. 57-72. Shehory, O., Sycara, K.P., and Jha, S., 1998. Multi-agent coordination through coalition formation. In Singh, M.P., Rao, A.S., and Wooldridge, M.J., (Eds.). Proceedings of ATAL’97, Springer Verlag. pp 143-154. Wildemann, H., 2001. Das Just-In-Time Konzept – Produktion und Zulieferung auf Abruf, TCW Transfer- Centrum GmbH. Muenchen, 5 th edition.
126 ENTERPRISE INFORMATION SYSTEMS VI Wildemann, H., 2003. Produktordnungssysteme: Leitfaden zur Standardisierung und Individualisierung des Produktprogramms durch intelligente Plattformstrategien, TCW Transfer-Centrum GmbH. Muenchen, 2 nd edition. Wooldrige, M., 2000. Reasoning about rational agents, The MIT Press. Cambridge et al.
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vi TABLE OF CONTENTS PART 1 - DATAB
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viii TABLE OF CONTENTS A WIRELESS A
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CONFERENCE COMMITTEE Honorary Presi
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Hung, P. (AUSTRALIA) Jahankhani, H.
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Invited Papers
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2 ENTERPRISE INFORMATION SYSTEMS VI
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EVOLUTIONARY PROJECT MANAGEMENT: MU
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MANAGING COMPLEXITY OF ENTERPRISE I
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ASSESSING EFFORT PREDICTION MODELS
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ORGANIZATIONAL AND TECHNOLOGICAL CR
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ASAP Processes W Project Kickoff A
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since it means changing the relevan
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BALANCING STAKEHOLDER’S PREFERENC
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The scenarios will provide an abstr
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BALANCING STAKEHOLDER'S PREFERENCES
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BALANCING STAKEHOLDER'S PREFERENCES
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A POLYMORPHIC CONTEXT FRAME TO SUPP
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A POLYMORPHIC CONTE XT FRAME TO SUP
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FEATURE MATCHING IN MODEL-BASED SOF
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combination of solution domains - a
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• features for all the concepts:
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Existence In both steps it is possi
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matching strategies are maximal, mi
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TOWARDS A META MODEL FOR DESCRIBING
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elementary message (ae-message) can
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problems on a pragmatic level, whic
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TOWARDS A META MODEL FOR DESCRIBING
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INTRUSION DETECTION SYSTEMS USING A
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INTRUSION DETECTION SYSTEMS USING A
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(k� 1) (k) (k�1) (k) p � w
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Table 5: Performance Comparison of
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A USER-CENTERED METHODOLOGY TO GENE
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carries out the second phase of the
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1 1 1 1 2 PROCESS STORE ENTITY EDGE
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constraints rules. KOGGE (Ebert et
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PART 4 Software Agents and Internet
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CABA 2 L A BLISS PREDICTIVE COMPOSI
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y disables evidencing severe mental
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Figure 4: Symbols emission in DAR-H
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they evidence a generalization erro
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A METHODOLOGY FOR INTERFACE DESIGN
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and mobility loss coupled with redu
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Tradeoff: The default input is poss
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Sessions on the VABS which are held
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A CONTACT RECOMMENDER SYSTEM FOR A
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A CONTACT RECOMMENDER SYSTEM FOR A
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- "Going to the sources". The user
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Here are the matrix W and P for our
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EMOTION SYNTHESIS IN VIRTUAL ENVIRO
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theme turns out to be surprisingly
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6 FROM FEATURES TO SYMBOLS 6.1 Face
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sions are described by different em
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Electronic Imaging 2000 Conference
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to the accessibility problem for th
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Figure 3: Hierarchical View of the
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4 CONCLUSIONS AND FUTURE WORK On th
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PERSONALISED RESOURCE DISCOVERY SEA
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profile, the user defines his curre
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Abdelkafi, N. .....................
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