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Concept of a Multi-Agent System for Assisting in Real Estate Appraisals

  • Conference paper
Agent and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2009)

Abstract

The general architecture of a multi-agent system for real estate appraisal (MAREA) is presented in the paper. The appraisal data warehouse is filled with data drawn from source cadastral databases. Data driven appraisal models are created using different machine learning algorithms. Architecture of the MAREA system in the JADE platform was also proposed. Several experiments aimed to assess the usefulness of different machine learning algorithms for the system were conducted using the KEEL tool.

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References

  1. Alcalá-Fdez, J., Sánchez, L., García, S., del Jesus, M.J., Ventura, S., Garrell, J.M., Otero, J., Romero, C., Bacardit, J., Rivas, V.M., Fernández, J.C., Herrera, F.: KEEL: A software tool to assess evolutionary algorithms for data mining problems. Soft Computing 13(3), 307–318 (2009)

    Article  Google Scholar 

  2. Alonso, E., d ’ Inverno, M., Kudenko, D., Luck, M., Noble, J.: Learning in multi-agent systems. Knowledge Engineering Review 16(3), 277–284 (2001)

    Article  Google Scholar 

  3. Bellifemine, F., Caire, G., Poggi, A., Rimassa, G.: JADE. A White Paper. EXP. 3(3), 6–19 (2003)

    MATH  Google Scholar 

  4. Casillas, J., Cordón, O., Herrera, F.: COR: A methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules. IEEE Trans. Syst. Man Cybern. Part B: Cybernetics 32(4), 526–537 (2002)

    Article  Google Scholar 

  5. Cordón, O., Herrera, F.: A Three-Stage Evolutionary Process for Learning Descriptive and Approximate Fuzzy Logic Controller Knowledge Bases from Examples. Int. J. Approximate Reasoning 17(4), 369–407 (1997)

    Article  MATH  Google Scholar 

  6. Fan, R.E., Chen, P.H., Lin, C.J.: Working set selection using the second order information for training SVM. Journal of Machine Learning Research 6, 1889–1918 (2005)

    MATH  Google Scholar 

  7. FIPA Agent Management Specification (Standard), Foundation for Intelligent Physical Agents, Geneva (2004)

    Google Scholar 

  8. Mannor, S., Shamma, J.S.: Multi-agent learning for engineers. Artificial Intelligence 171(7), 417–422 (2007)

    Google Scholar 

  9. Król, D., Lasota, T., Nalepa, W., Trawiński, B.: Fuzzy system model to assist with real estate appraisals. In: Okuno, H.G., Ali, M. (eds.) IEA/AIE 2007. LNCS(LNAI), vol. 4570, pp. 260–269. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  10. Król, D., Lasota, T., Trawiński, B., Trawiński, K.: Investigation of evolutionary optimization methods of TSK Fuzzy Model for Real Estate Appraisal. International Journal of Hybrid Intelligent Systems 5(3), 111–128 (2008)

    Article  MATH  Google Scholar 

  11. Kudenko, D., Kazakov, D., Alonso, E.: Machine Learning for Agents and Multi-Agent Systems. In: Plekhanova, V. (ed.) Intelligent Agent Software Engineering. Idea Group Publishing (2002)

    Google Scholar 

  12. Lasota, T., Mazurkiewicz, J., Trawiński, B., Trawiński, K.: Investigation of Fuzzy Models for the Valuation of Residential Premises using the KEEL Tool. In: Proceedings of the Eighth International Conference on Hybrid Intelligent Systems (HIS 2008), pp. 258–263. IEEE, Los Alamitos (2008)

    Chapter  Google Scholar 

  13. Lasota, T., Trawiński, B., Trawiński, K.: An attempt to use the KEEL tool to evaluate fuzzy models for real estate appraisal. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds.) New Trends in Multimedia and Network Information Systems, pp. 125–139. IOS Press, Amsterdam (2008)

    Google Scholar 

  14. Moller, F.: A scaled conjugate gradient algorithm for fast supervised learning. Neural Networks 6, 525–533 (1990)

    Article  Google Scholar 

  15. Nwana, H.S.: Software Agents: An Overview. Knowledge Engineering Review 11(3), 205–244 (1996)

    Article  Google Scholar 

  16. Panait, L., Luke, S.: Cooperative Multi-Agent Learning: The State of the Art. Autonomous Agents and Multi-Agent Systems 11(3), 387–434 (2005)

    Article  Google Scholar 

  17. Quinlan, J.R.: Learning with Continuous Classes. In: 5th Australian Joint Conference on Artificial Intelligence (AI 1992), Singapore, pp. 343–348 (1992)

    Google Scholar 

  18. Rustagi, J.S.: Optimization Techniques in Statistics. Academic Press, London (1994)

    MATH  Google Scholar 

  19. Stone, P., Veloso, M.: Multiagent systems: A survey from a machine learning perspective. Autonomous Robotics 8(3), 345–383 (2000)

    Article  Google Scholar 

  20. Wang, L.X., Mendel, J.M.: Generating Fuzzy Rules by Learning from Examples. IEEE Transactions on Systems, Man and Cybernetics 22(6), 1414–1427 (1992)

    Article  MathSciNet  Google Scholar 

  21. Wooldridge, M.J., Jennings, N.R.: Intelligent agents: Theory and practice. Knowledge Engineering Review 10(2), 115–152 (1995)

    Article  Google Scholar 

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Lasota, T., Telec, Z., Trawiński, B., Trawiński, K. (2009). Concept of a Multi-Agent System for Assisting in Real Estate Appraisals. In: Håkansson, A., Nguyen, N.T., Hartung, R.L., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2009. Lecture Notes in Computer Science(), vol 5559. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01665-3_6

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  • DOI: https://doi.org/10.1007/978-3-642-01665-3_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01664-6

  • Online ISBN: 978-3-642-01665-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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