Intelligent Market Based Learner Modeling

  • Maryam Ashoori
  • Chun Yan Miao
  • Angela Eck Soong Goh
  • Wang Qiong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4099)


This paper presents an economical inspired intelligent approach for modeling learners in learning systems. Decision making in complex systems like e-learning systems requires processing of large amounts of heterogeneous data and information from dispread sources. Moreover, most of the decision parameters are incomplete and uncertain. Lacking of a complete model of learner is the prominent problem of current learning systems. In this paper, a market based method for describing Learner’s preferences to the learning system is provided. The proposed approach strives for applying a Dempster-Shafer decision making over a society of self motivated agents. It tries to present a final learner agent with a high degree of similarity to the user for the purpose that it can act as a model of learner through the system. An implicit learning is also implemented by the idea of Stocks in real markets which can improve decision making efficiently.


Total Asset Implicit Learning Agent Selection Learner Agent Negotiation Protocol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Maryam Ashoori
    • 1
  • Chun Yan Miao
    • 1
  • Angela Eck Soong Goh
    • 1
  • Wang Qiong
    • 2
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingapore
  2. 2.School of EducationPeking UniversityChina

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