Intelligent Market Based Learner Modeling
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.
KeywordsTotal Asset Implicit Learning Agent Selection Learner Agent Negotiation Protocol
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