Abstract
Hierarchical structure, reusable and dynamic components, and predictable interactions are distinct characteristics of hybrid intelligent systems (HIS). The existing agent-oriented methodologies are deficient in HIS construction because they did not take into account the characteristics of HIS. In this paper, we propose a Methodology for constructing Agent-based HIS (MAHIS). MAHIS consists of eight models: Hybrid Strategy Identification Model, Organization Model, Task Model, Agent Model, Expertise Model, Coordination Model, Reorganization Model, and Design Model. The Reorganization Model is the key model to support dynamic platform-based HIS. It consists of category role, group roles, virtual organization role, and dynamics rules. This model describes the characteristics of HIS with virtual organization, category, and group perspectives. Some previously developed agents can be reused by means of involving them in a new virtual organization dynamically. The output of the Reorganization Model is the specification of the dynamic platform which comprises middle agents and makes all agents and agent groups hierarchical and dynamic.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Zhang, Z., Zhang, C.: Agent-Based Hybrid Intelligent Systems. LNCS (LNAI), vol. 2938, pp. 57–64. Springer, Heidelberg (2004)
Centeno-Gonzalez, J., Velasco, J.R., Iglesias, C.A.: An agent-based operational model for hybrid connectionist-symbolic learning. Presented at the International Work-Conference on Artificial and Natural Neural Networks, Alicante, Spain (1999)
Khosla, R., Dillon, T.: Engineering intelligent hybrid multi-agent systems. Kluwer Academic Publishers, Boston (1997)
Li, C., Liu, L., Song, Q.: A practical framework for agent-based hybrid intelligent systems. Asian Journal of Information Technology 3, 107–114 (2004)
Sturm, A., Shehory, O.: A framework for evaluating agent-oriented methodologies. In: Giorgini, P., Henderson-Sellers, B., Winikoff, M. (eds.) AOIS 2003. LNCS (LNAI), vol. 3030, pp. 94–109. Springer, Heidelberg (2004)
Bauer, B., Muller, J.P., Odell, J.J.: Agent UML: a formalism for specifying multiagent interaction. In: Ciancarini, P., Wooldridge, M. (eds.) Agent-Oriented Software Engineering, pp. 91–103. Springer, Berlin (2001)
Iglesias, C.A., Garijo, M., Centeno-Gonzalez, J., Velasco, J.R.: Analysis and design of multiagent systems using MAS-CommonKADS. Presented at 4th International Workshop, ATAL 1997, Providence, Rhode Island, USA (1997)
Rudolph, E., Graubman, P., Grabowski, J.: Tutorial on Message Sequence Charts. Computer Networks and ISDN Systems 28, 1629–1641 (1996)
Finin, T., Labrou, Y., Mayfield, J.: KQML as an agent communication language. In: Brashaw, J.M. (ed.) Software Agents, pp. 291–316. AAAI Press/The MIT Press (1997)
Mrhailaf, R., Sahraoui, A.: DFD extended methods for specifying hybrid systems. Presented at the International Conference on Systems, Man and Cybernetics, Le Touquet France (1993)
Schreiber, G., Akkermans, H., Anjewierden, A., der Hoog, R., Shadbolt, N., van der Velde, W.: Knowledge engineering and management: the CommonKADS methodology. MIT Press, Cambridge (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, C., Liu, L. (2005). MAHIS: An Agent-Oriented Methodology for Constructing Dynamic Platform-Based HIS. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_73
Download citation
DOI: https://doi.org/10.1007/11589990_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30462-3
Online ISBN: 978-3-540-31652-7
eBook Packages: Computer ScienceComputer Science (R0)