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References ACT-R 6.0 Tutorial. 2012. Unpublished manuscript. Retrieved from http://actr.psy.cmu.edu/wordpress/wp-content/themes/ACT-R/actr6/actr6.zip Albus, J. S., and Barbera, A. J. 2005. RCS: A cognitive architecture for intelligent multi-agent systems. Annual Reviews in Control, 29(1):87-99. Anderson, J. 2007. How can the human mind occur in the physical universe? : Oxford University Press. Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., and Qin, Y. 2004. An integrated theory of the mind. Psychological Review, 111

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Journal of Artificial General Intelligence 3(2) 31-63, 2012 DOI: 10.2478/v10229-011-0016-2 Submitted 2012-06-07 Accepted 2012-10-07 © 2012 Duch et al; Distributed under Creative Commons Attribution License Cognitive Architectures and Autonomy: Commentary and Response Editor: Włodzisław Duch, Ah-Hwee Tan, Stan Franklin Autonomy for AGI Cristiano Castelfranchi ISTC-CNR Italy CRISTIANO.CASTELFRANCHI@ISTC.CNR.IT This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems

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http://www.idsia.ch/~juergen/gmweb3/gmweb3.html Schmidhuber, J. (2004). Optimal Ordered Problem Solver. Machine Learning, 54, 211–254. Kluwer Academic Publishers. Skaba, W. (2011). Heuristic Search in Program Space for the AGINAO Cognitive Architecture. AGI 2011 Self-Programming Workshop. Available electronically at http://www.iiim.is/wp/wp-content/uploads/2011/05/skaba-agisp-2011.pdf Skaba, W. (2012). Binary Space Partitioning as Intrinsic Reward. Proceedings of Artificial General Intelligence 2012. LNAI 7716, Springer-Verlag. Sutton R. S. and Barto A. G. (1998

Method]. Warsaw: Academica. Stemplewska-Żakowicz, K., Suszek, H., Kobylińska, D., & Szymczyk, B. (2010). Explorations in the discursive mind. Th eoretical model. International Journal for Dialogical Science, 4 (1), 81-94. Stemplewska-Żakowicz, K., Zalewski, B., Suszek, H., Fira-Krempa, E., & Kobylińska, D. (2009). Relacyjnie strukturalizowany umysł. Model Teoretyczny [Relationally structured mind. A theoretical model]. Przegląd Psychologiczny, 52 (1), 69-85. Stemplewska-Żakowicz, K., Zalewski, B., Suszek, H., & Kobylińska, D. (2012). Cognitive architecture of the

Abstract

This paper describes a design-based implementation research (DBIR) approach to the development and trialling of a new generation massive open online course (ngMOOC) situated in an instructional setting of undergraduate mathematics at a regional Australian university. This process is underscored by two important innovations: (a) a basis in a well-established human cognitive architecture in terms of cognitive load theory; and (b) point-of-contact feedback based in a well-tested online system dedicated to enhancing the learning process. Analysis of preliminary trials suggests that the DBIR approach to the ngMOOC construction and development supports theoretical standpoints that argue for an understanding of how design for optimal learning can utilise conditions, such as differing online or blended educational contexts, in order to be effective and scalable. The ngMOOC development described in this paper marks the adoption of a cognitive architecture in conjunction with feedback systems, offering the groundwork for use of adaptive systems that cater for learner expertise. This approach seems especially useful in constructing and developing online learning that is self-paced and curriculum-based.

., & Schooler, L. J. (1991). Reflections of the environment in memory. Psychological Science, 2, 396-408. Ball, J. T., Myers, C. W., Heiberg, A., Cooke, N. J., Matessa, M., Freiman, M., et al. (under review). The Synthetic Teammate Project. Computational and Mathematical Organization Theory . Byrne, M. D. (2003). Cognitive Architecture. In J. Jacko & A. Sears (Eds.), The human-computer interaction handbook: Fundamentals, evolving technologies and emerging applications (pp. 97-117). Mahwah, NJ: Lawrence Erlbaum. Dimperio, E., Gunzelmann, G., & Harris, J. (2008). An initial