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Applied Decision Support with Soft Computing pp 99–126Cite as

An Agent-based Soft Computing Society with Applications in Financial Investment Planning

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 124))

Abstract

Solving problems and making decisions effectively have far-reaching influence on a nation, an organization, or a person. It is not easy work to do for complex problems such as financial investment planning. Many complex problems have many different components, each of which requires different types of processing. That is, hybrid solutions are crucial for complex problem solving and decision making. On the other hand, hybrid intelligent systems are complex because they have a large number of parts or components that have many interactions, whereas multi-agent systems (MAS) are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. To this end, this chapter discusses the details of the analysis, design, and implementation of an agent-based hybrid intelligent system (called agent-based soft computing society) for complex problem solving and decision making according to the available agent-oriented software engineering methodologies. The applications of the society in financial investment planning are also addressed.

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References

  1. S. Russell and P. Norvig, A Modern Approach to Artificial Intelligence, Pretice-Hall, 1995.

    Google Scholar 

  2. E. H. Durfee and V. Lesser, Negotiating Task Decomposition and Allocation Using Partial Global Planning, in: L. Gasser and M. Huhns (Eds.), Distributed Artificial Intelligence Volume II, Pitman Publishing and Morgan Kaufmann, 1989, 229 - 244.

    Google Scholar 

  3. A. Cheyer and D. Martin, The Open Agent Architecture, Autonomous Agents and Multi-Agent Systems, Vol. 4, No. 1-2, 2001, 143 - 148.

    Article  Google Scholar 

  4. V. Subrahmanian, P. Bonatti, J. Dix, et al., Heterogeneous Agent Systems, The MIT Press, 2000.

    Google Scholar 

  5. R. J. Bayardo, W. Bohrer, R. Brice et al., InfoSleuth: Agent-Based Semantic Integration of Information in Open and Dynamic Environments, in: M. N. Huhns and M. P. Singh (Eds.), Readings in Agents, Morgan Kaufmann, CA, 1998, 205 - 216.

    Google Scholar 

  6. M. Hilario, C. Pellegrini, and F. Alexandre, Modular Integration of Connectionist and Symbolic Processing in Knowledge-based Systems, in: Int. Symposium on Integrating Knowledge and Neural Heuristics, Pensacola, Florida, 1994, 123 - 132.

    Google Scholar 

  7. A. Scherer and G. Schlageter, A Multi-Agent Approach for the Integration of Neural Networks and Expert Systems, in: S. Goonatilake and S. Khebbal (Eds.), Intelligent Hybrid Systems, Wiley, 1995, 153 - 173.

    Google Scholar 

  8. R. Khosla and T. Dillon, Engineering Intelligent Hybrid Multi-Agent Systems, Kluwer Academic Publishers, Boston, 1997.

    Book  MATH  Google Scholar 

  9. M. Delgado, A. F. Gómez-Skarmeta et al., A Multi-Agent Architecture for Fuzzy Modeling, International Journal of Intelligent Systems, Vol. 14, 1999, 305 - 329.

    Article  MATH  Google Scholar 

  10. K. Decker, K. Sycara, and M. Williamson, Middle Agents for the Internet, Proceedings of 15th International Joint Conference on Artificial Intelligence, Nogoya, Japan, 1997, 578 - 583.

    Google Scholar 

  11. A. Newell, The Knowledge Level, Artificial Intelligence, Vol. 18, 1982, 87 - 127.

    Article  Google Scholar 

  12. S. Goonatilake and S. Khebbal (Eds.), Intelligent Hybrid Systems, Wiley, 1995.

    Google Scholar 

  13. L. R. Medsker, Hybrid Intelligent Systems, Kluwer Academic Publisher, 1995.

    Google Scholar 

  14. L. C. Jain and R. K. Jain (Eds.), Hybrid Intelligent Engineering Systems, World Scientific, Singapore, 1997.

    MATH  Google Scholar 

  15. N. Lertpalangsunti and C. W. Chan, An Architecture Framework for the Construction of Hybrid Intelligent Forecasting Systems: Application for Electricity Demand prediction, Engineering Applications of Artificial Intelligence, Vol. 11, No. 4, 1998, 549 - 565.

    Article  Google Scholar 

  16. S. Li, The Development of a Hybrid Intelligent Systems for Developing Marketing Strategy, Decision Support Systems, Vol. 27, No. 4, 2000, 395 - 409.

    Article  Google Scholar 

  17. M. Wooldrige, N. Jennings, and D. Kinny, The Gaia Methodology for Agent-Oriented Analysis and Design, Journal of Autonomous Agents and Multi-Agent Systems, Vol. 3, No. 3, 2000, 285 - 312.

    Article  Google Scholar 

  18. C. Iglesias, J. Gonzales, and J. Velasco, MIX: A General Purpose Multiagent Architecture, in: M. Wooldridge, J. Muller, and M. Tambe (Eds.), Intelligent Agents II (ATAL95), LNCS 1037, Springer, 1996, 251 - 266.

    Google Scholar 

  19. H.-A. Jacobsen, A Generic Architecture for Hybrid Intelligent Systems, in: T. Furuhashi et al. (Eds.), Deep Fusion of Computational and Symbolic Processing, Physica-Verlag, 2001, 145 - 173.

    Google Scholar 

  20. Z. Zhang and C. Zhang, Considering Agents Track Records in Matchmaking of Middle Agents, Proceedings of 4th Pacific Rim International Workshop on Multi-Agents, Taipei, 2001, 281 - 292.

    Google Scholar 

  21. G. Bojadziev and M. Bojadziev, Fuzzy Logic For Business, Finance, and Management, World Scientific, Singapore, 1997.

    Book  MATH  Google Scholar 

  22. C. Zhang, Z. Zhang, and S. Ong, An Agent-Based Soft Computing Society, Proceedings of 2nd International Conference on Rough Sets and Current Trends in Computing, Banff, Canada, 2000, 621 - 628.

    Google Scholar 

  23. R. R. Yager, On Ordered Weighted Averaging Aggregation Operators in Multi-criteria Decision Making, IEEE Transactions on Systems, Man, Cybernetics, Vol. 18, Jan/Feb, 1988, 183 - 190.

    Google Scholar 

  24. Z. Zhang and C. Zhang, Result Fusion in Multi-Agent Systems Based on OWA Operator, Proceedings of 23rd Australasian Computer Science Conference, IEEE Computer Society Press, NJ, 2000, 234 - 240.

    Google Scholar 

  25. Stephen T. Welstead, Neural Network and Fuzzy Logic Applications in C/C++, Wiley, New York, 1994, 395 - 421.

    Google Scholar 

  26. H. Markowitz, Portfolio Selection: Efficient Diversification of Investments (2nd ed.), Blackwell, 1991.

    Google Scholar 

  27. H. Tanaka, P. Guo, and I. Turksen, Portfolio Selection Based on Fuzzy Probabilities and Possibility Distributions, Fuzzy Sets and Systems, Vol. 111, 2000, 387 - 397.

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Information Technology, University of Technology, Sydney, PO Box 123, Broadway, 2007, NSW, Australia

    Chengqi Zhang

  2. School of Computing and Mathematics, Deakin University, Geelong, 3217, VIC, Australia

    Zili Zhang

  3. Computer Science Department, Southwest China Normal University, Chongqing, 400715, China

    Zili Zhang

Authors
  1. Chengqi Zhang
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  2. Zili Zhang
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Editor information

Editors and Affiliations

  1. Faculty of Engineering, Royal Melbourne Institute of Technology, GPO Box 2476V, 3001, Melbourne, VIC, Australia

    Xinghuo Yu

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

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© 2003 Springer-Verlag Berlin Heidelberg

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Zhang, C., Zhang, Z. (2003). An Agent-based Soft Computing Society with Applications in Financial Investment Planning. In: Yu, X., Kacprzyk, J. (eds) Applied Decision Support with Soft Computing. Studies in Fuzziness and Soft Computing, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37008-6_4

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  • DOI: https://doi.org/10.1007/978-3-540-37008-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53534-5

  • Online ISBN: 978-3-540-37008-6

  • eBook Packages: Springer Book Archive

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