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Issue No.03 - May/June (2009 vol.24)
pp: 46-53
Roger Nkambou , University of Quebec
Philippe Fournier-Viger , University of Quebec
Engelbert Mephu Nguifo , Université Blaise- Pascal, Clermont-Ferrand II
This article presents a novel framework for adapting the behavior of intelligent agents. The framework consists of an extended sequential pattern mining algorithm that, in combination with association rule discovery techniques, is used to extract temporal patterns and relationships from the behavior of human agents executing a procedural task. The proposed framework has been integrated within the CanadarmTutor, an intelligent tutoring agent aimed at helping students solve procedural problems that involve moving a robotic arm in a complex virtual environment. We present the results of an evaluation that demonstrates the benefits of this integration to agents acting in ill-defined domains.
data mining, intelligent agent, intelligent tutoring systems, cognitive agent, knowledge acquisition, knowledge discovery
Roger Nkambou, Philippe Fournier-Viger, Engelbert Mephu Nguifo, "Improving the Behavior of Intelligent Tutoring Agents with Data Mining", IEEE Intelligent Systems, vol.24, no. 3, pp. 46-53, May/June 2009, doi:10.1109/MIS.2009.59
1. H.A. Simon, "Information-Processing Theory of Human Problem Solving," Handbook of Learning and Cognitive Processes, vol. 5,W.K. Estes, ed., Lawrence Erlbaum Associates, 1978.
2. K.-L. Ong et al., "Agents and Stream Data Mining: A New Perspective," IEEE Intelligent Systems, vol. 20, no. 3, 2005, pp. 60–67.
3. P. Fournier-Viger, R. Nkambou, and E. Mephu Nguifo, "A Knowledge Discovery Framework for Learning Task Models from User Interactions in Intelligent Tutoring Systems," Proc. 7th Mexican Int'l Conf. Artificial Intelligence (MICAI 08), LNAI 5317, Springer, 2008, pp. 765–778.
4. J. Pei et al., "Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach," IEEE Trans. Knowledge and Data Eng., vol. 16, no. 11, 2004, pp. 1424–1440.
5. A.D. Lattner et al., "Sequential Pattern Mining for Situation and Behavior Prediction in Simulated Robotic Soccer," Proc. 9th Robot Soccer World Cup Conf. (RoboCup 05), Springer, 2005, pp. 118–129.
6. G. Gasmi et al., "A New Informative Generic Base of Association Rules," Proc. 9th Pacific-Asia Conf. Knowledge Discovery and Data Mining (PAKDD 05), Springer, 2005, pp. 81–90.
7. F. Kabanza, R. Nkambou, and K. Belghith, "Path-Planning for Autonomous Training on Robot Manipulators in Space," Proc. 19th Int'l Joint Conf. Artificial Intelligence (IJCAI 05), Professional Book Center, 2005, pp. 1729–1731.
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