Abstract
To mimic human tutor and provide optimal training, an intelligent tutoring agent should be able to continuously learn from its interactions with learners. Up to now, the learning capabilities of tutoring agents in educational systems have been generally very limited. In this paper, we address this issue with CELTS, a cognitive tutoring agent, whose architecture is inspired by the latest neuroscientific theories and unite several human learning capabilities such as episodic, emotional, procedural and causal learning.
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References
Woolf, B.P.: Building Intelligent Interactive Tutors. Student Centered Strategies for revolutionizing e-learning. Morgan Kaufmann, Massachusetts (2009)
Faghihi, U., poirier, P., Fournier-Viger, P., Nkambou, R.: Human-Like Learning in a Conscious Agent. Journal of Experimental & Theoretical Artificial Intelligence (2010) (in Press)
Tulving, E.: Precis of Elements of Episodic Memory. Behavioural and Brain Sciences 7, 223–268 (1984)
Purves, D., Brannon, E., Cabeza, R., Huettel, S.A., LaBar, K., Platt, M., Woldorff, M.: Principles of cognitive neuroscience. In: First, E. (ed.), Sunderland. Sinauer Associates, Massachusetts (2008)
Gopnik, A., Schulz, L. (eds.): Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press, USA (2007)
Maldonado, A., Catena, A., Perales, J.C., Cándido, A.: Cognitive Biases in Human Causal Learning (2007)
Brauny, M., Rosenstiel, W., Schubert, K.-D.: Comparison of Bayesian Networks and Data Mining for Coverage Directed Verification. IEEE, Los Alamitos (2003)
Faghihi, U., Fournier-Viger, P., Nkambou, R., Poirier, P.: A Generic Causal Learning Model for Cognitive Agent. In: The Twenty Third International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems, IEA-AIE 2010 (2010)
LeDoux, J.E.: Emotion circuits in the brain. Annu. Rev. Neurosci. 2000 23, 155–184 (2000)
Morén, J.: Emotion and learning: a computational model of the amygdala. Lund University, Lund (2002)
Phelps, E.A.: Emotion and Cognition: Insights from studies of the human amygdala. Annual Review of Psychology 57, 27–53 (2006)
Baars, B.J.: In the Theater of Consciousness: The Workspace of the Mind. Oxford University Press, Oxford (1997)
Nkambou, R., Belghith, K., Kabanza, F.: An approach to intelligent training on a robotic simulator using an innovative path-planner. In: Ikeda, M., Ashley, K.D., Chan, T.-W. (eds.) ITS 2006. LNCS, vol. 4053, pp. 645–654. Springer, Heidelberg (2006)
Maes, P.: How to do the right thing. Connection Science 1, 291–323 (1989)
Thompson, R.F., Madigan, S.A.: Memory: The Key to Consciousness. Princeton University Press, Princeton (2007)
Alvarado, N., Adams, S., Burbeck, S.: The Role Of Emotion In An Architecture Of Mind. IBM Research (2002)
Damasio, A.R.: Looking for Spinoza: Joy, Sorrow and the Feeling Brain. Harcourt Inc., New York (2003)
Martin, C.B., Deutscher, M.: Remembering. Philosophical Review 75, 161–196 (1966)
Shoemaker, S.: Persons and their Pasts. American Philosophical Quarterly 7, 269–285 (1970)
Perner, J.: Memory and Theory of Mind. In: Tulving, E., Craik, F.I.M. (eds.) The Oxford Handbook of Memory, pp. 297–312. Oxford University Press, Oxford (2000)
Bernecker, S.: The Metaphysics of Memory. Springer, Berlin (2008)
Schoppek, W.: Stochastic Independence between Recognition and Completion of Spatial Patterns as a Function of Causal Interpretation. In: Proceedings of the 24th Annual Conference of the Cognitive Science Society (2002)
Schoppek, W.: Stochastic independence between recognition and completion of spatial patterns as a function of causal interpretation. In: Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp. 804–809. Erlbaum, Mahwah (2002)
Anderson, J.R., Bothell, D., Byrne, M.D., Douglass, S., lebiere, C., Qin, Y.: An integrated theory of the mind. Psychological Review 111(4), 1036–1060 (2004)
Gopnik, A., Glymour, C., Sobel, D.M., Schulz, L.E., Kushnir, T., Danks, D.: A Theory of Causal Learning in Children: Causal Maps and Bayes Nets. Psychological Review 111(1) (2004)
Braun, M., Rosenstiel, W., Schubert, K.-D.: Comparison of Bayesian networks and data mining for coverage directed verification category simulation-based verification. In: Eighth IEEE International, High-Level Design Validation and Test Workshop, 2003, pp. 91–95 (2003)
Hipp, J., Güntzer, U., Nakhaeizadeh, G.: Data Mining of Association Rules and the Process of Knowledge Discovery in Databases. In: Industrial Conference on Data Mining, pp. 15–36 (2002)
Deogun, J.S., Jiang, L.: Prediction Mining – An Approach to Mining Association Rules for Prediction. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W.P., Hu, X. (eds.) RSFDGrC 2005. LNCS (LNAI), vol. 3642, pp. 98–108. Springer, Heidelberg (2005)
Li, L., Deogun, J.S.: Discovering Partial Periodic Sequential Association Rules with Time Lag in Multiple Sequences for Prediction. In: Hacid, M.-S., Murray, N.V., Raś, Z.W., Tsumoto, S. (eds.) ISMIS 2005. LNCS (LNAI), vol. 3488, pp. 332–341. Springer, Heidelberg (2005)
Fournier-viger, P., Nkambou, R., Tseng, V.S.: RuleGrowth: Mining Sequential Rules Common to Several Sequences by Pattern-Growth. In: Proceedings of the 26th Symposium on Applied Computing (ACM SAC 2011), pp. 954–959 (2011)
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Faghihi, U., Fournier-Viger, P., Nkambou, R. (2011). A Cognitive Tutoring Agent with Episodic and Causal Learning Capabilities. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_12
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DOI: https://doi.org/10.1007/978-3-642-21869-9_12
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