My Research: skill learning

List of Publications on Skill Learning

Journal Papers:

• • N. Wilson and R. Sun, A mechanistic account of stress-induced performance degradation. Cognitive Computation, in press. https://rdcu.be/b34GG https://dx.doi.org/10.1007/s12559-020-09725-5

  • S. Helie and R. Sun, Incubation, insight, and creative problem solving: A unified theory and a connectionist model. Psychological Review, Vol.117, No.3, pp.994-1024. 2010.

  • R. Sun, Autonomous generation of symbolic representations through subsymbolic activities. Philosophical Psychology, Vol.26, No.6, pp.888-912. 2013. [formatted PDF]

  • N. Wilson, R. Sun, and R. Mathews, A motivationally-based simulation of performance degradation under pressure . Neural Networks, Vol.22, pp.502-508. 2009.

  • R. Sun, X. Zhang, and R. Mathews, Capturing human data in a letter counting task: Accessibility and action-centeredness in representing cognitive skills . Neural Networks, Vol.22, pp.15-29. 2009.

  • S. Lane, R. Mathews, B. Sallas, R. Prattini, and R. Sun, Facilitative interactions of model- and experience-based processes: Implications for type and flexibility of representation . Memory and Cognition, Vol.36, No.1, pp.157-169. 2008.

  • B. Sallas, R. Mathews, S. Lane, and R. Sun, Developing rich and quickly accessed knowledge of an artificial grammar . Memory and Cognition, Vol.35, No.8, pp.2118-2133. 2007.

  • R. Sun, X. Zhang, P. Slusarz, and R. Mathews, The interaction of implicit learning, explicit hypothesis testing learning, and implicit-to-explicit knowledge extraction . Neural Networks, Vol.20, No.1, pp.34-47. 2007. [Elsevier formatted PDF]

  • I. Naveh and R. Sun, A cognitively based simulation of academic science . Computational and Mathematical Organization Theory, Vol.12, pp.313-337. 2006.

  • R. Sun, P. Slusarz, and C. Terry, The interaction of the explicit and the implicit in skill learning: A dual-process approach. Psychological Review, Vol.112, No.1, pp.159-192. 2005.

  • R. Sun and D. Qi, MARLBS: Team cooperation through bidding . International Journal of Computational Intelligence Research, Vol.1, No.1, pp.42-58. 2005. [formatted PDF]

  • D. Qi and R. Sun, Learning to cooperate in solving the traveling salesman problem. International Journal of Neural Systems, Vol.15, No.1&2, pp.151-162. 2005.

  • R. Sun and X. Zhang, Top-down versus bottom-up learning in cognitive skill acquisition. Cognitive Systems Research, Vol.5, No.1, pp.63-89, March 2004. [Elsevier-formatted PDF]

  • T. Domangue, R. Mathews, R. Sun, L. Roussel, and C. Guidry, The effects of model-based and memory-based processing on speed and accuracy of grammar string generation . Journal of Experimental Psychology: Learning, Memory, and Cognition, 30 (5), pp.1002-1011. 2004.

  • R. Sun and I. Naveh, Simulating organizational decision-making using a cognitively realistic agent model. Journal of Artificial Societies and Social Simulation, Vol.7, No.3. 2004. [ http://jasss.soc.surrey.ac.uk/7/3/5.html ]

  • R. Sun, E. Merrill, and T. Peterson, From implicit skills to explicit knowledge: a bottom-up model of skill learning Cognitive Science, Vol.25, No.2, pp.203-244. 2001. [ PDF] [Elsevier-formatted PDF]

  • R. Sun and L. Giles, Sequence learning: From prediction and recognition to sequential decision making. IEEE Intelligent Systems, Vol.16, No.4, pp.67-70. July/August, 2001. [formatted PDF]

  • R. Sun and C. Sessions, Learning plans without a priori knowledge. Adaptive Behavior, Vol.8, No.3/4, pp.225-253. 2000. [formatted PDF]

  • R. Sun and C. Sessions, Self-segmentation of sequences: Automatic formation of hierarchies of sequential behaviors. IEEE Transactions on Systems, Man, and Cybernetics: Part B Cybernetics, Vol.30, No.3, pp.403-418. 2000. [PDF]

  • R. Sun and T. Peterson, Multi-agent reinforcement learning: Weighting and partitioning. Neural Networks, Vol.12, No.4-5. pp.127-153. 1999. [Elsevier-formatted PDF]

  • R. Sun, T. Peterson, and E. Merrill, A hybrid architecture for situated learning of reactive sequential decision making. Applied Intelligence, Vol.11, pp.109-127. 1999.

  • R. Sun and T. Peterson, Autonomous learning of sequential tasks: Experiments and analyses. IEEE Transactions on Neural Networks, Vol.9, No.6, pp.1217-1234. November, 1998. [PDF]

  • R. Sun and T. Peterson, Some experiments with a hybrid model for learning sequential decision making. Information Sciences. vol.111, pp.83-107. 1998.

Book Chapters:

• • R. Sun, R. Mathews, and S. Lane, Implicit and explicit processes in the development of cognitive skills: A theoretical interpretation with some practical implications for science education. In: E. Vargios (ed.), Educational Psychology Research Focus, pp.1-26. Nova Science Publishers, Hauppauge, NY. 2007.

  • R. Sun, Introduction to sequence learning. In: R. Sun and L. Giles, (eds.) Sequence Learning: Paradigms, Algorithms, and Applications. Springer-Verlag, Heidelberg, 2000.

  • R. Sun, E. Merrill, and T. Peterson, Knowledge acquisition via bottom-up skill learning. Knowledge Engineering: Systems, Techniques and Applications, ed. C. Leondes, Academic Press. 2000.

Papers in Conference Proceedings (Human Learning):

• • N. Wilson, R. Sun, and R. Mathews, A motivationally based computational interpretation of social anxiety induced stereotype bias . Proceedings of the Annual Conference of the Cognitive Science Society, pp.1750-1755. Cognitive Science Society, Austin, Texas. 2010.

  • S. Helie and R. Sun, Creative problem solving: A CLARION theory . Proceedings of the 2010 International Joint Conference on Neural Networks, Barcelona, Spain. pp.1460-1466. IEEE Press, Piscataway, NJ. 2010.

  • S. Helie and R. Sun, Simulating incubation effects using the explicit-implicit interaction with Bayes factor (EII-BF) Model . Proceedings of the International Joint Conference on Neural Networks, Atlanta, Georgia, USA. pp.1199-1205. IEEE Press, Piscataway, NJ. 2009.

  • S. Helie and R. Sun, Knowledge integration in creative problem solving. Proceedings of the 2008 Annual Conference of the Cognitive Science Society, Washington, DC. pp.1681-1686. Published by the Cognitive Science Society. July, 2008.

  • S. Helie, R. Sun, and L. Xiong, Mixed effects of distractor tasks on incubation. Proceedings of the 2008 Annual Conference of the Cognitive Science Society, Washington, DC. pp.1251-1256. Published by the Cognitive Science Society. July, 2008.

  • R. Sun and I. Naveh, A cognitively based simulation of simple organizations. Proceedings of the 27th Annual Conference of the Cognitive Science Society, Stresa, Italy. Lawrence Erlbaum Associates, Mahwah, NJ. 2005.

  • R. Sun and X. Zhang, Accessibility versus action-centeredness in the representation of cognitive skills. Proceedings of the Fifth International Conference on Cognitive Modeling. Bamberg, Germany, April 10-12, 2003 [ PDF]

  • R. Sun and C. Terry, Implicit learning of serial reaction time tasks: Connectionist vs. symbolic models. Proceedings of the 24th Annual Conference of the Cognitive Science Society, Fairfax, VA. Lawrence Erlbaum Associates, Mahwah, NJ. 2002. [ PDF]

  • R. Sun and X. Zhang, Top-down versus bottom-up learning in skill acquisition. Proceedings of the 24th Annual Conference of the Cognitive Science Society, Fairfax, VA. Lawrence Erlbaum Associates, Mahwah, NJ. 2002. [ PDF]

  • P. Slusarz and R. Sun, The interaction of explicit and implicit learning: An integrated model. Proceedings of Cognitive Science Society Conference, Edinburgh, pp.952-957. 2001. [ PDF]

  • R. Sun, E. Merrill, and T. Peterson, A bottom-up model of skill learning. Proceedings of the 20th Conference of Cognitive Science Society, August, 1998. pp.1037-1042. Lawrence Erlbaum Associates.

  • R. Sun, E. Merrill, and T. Peterson, Skill learning using a bottom-up hybrid model. Proceedings of The Second European Conference on Cognitive Modeling, Nottingham, UK. April, 1998.

  • R. Sun and T. Peterson, A symbolic+subsymbolic model for learning sequential navigation. Proceedings of the Fifth International Conference of the Society for Adaptive Behavior (SAB'98). Zurich, Switzerland. 1998. MIT Press.

  • R. Sun, An agent architecture for on-line learning of procedural and declarative knowledge. Proceedings of ICONIP'97, pp.766-769, Springer-Verlag. 1997.

  • R. Sun, E. Merrill, and T. Peterson, Skill learning using a bottom-up hybrid model. Proceedings of The First International Conference on Cognitive Science, Seoul, Korea. August 15-16, 1997. Also in: Proceedings of World Multiconference on Systemics, Cybernetics and Informatics (SCI'97), Caracas, Venezuela, July 7-11, 1997.

  • R. Sun, T. Peterson, and E. Merrill, Bottom-up skill learning in reactive sequential decision tasks. Proceedings of 18th Cognitive Science Society Conference, Lawrence Erlbaum Associates, Hillsdale, NJ. pp.684-690. 1996.

Other Conference Papers (Machine Learning):

• • D. Qi and R. Sun, A comparison of team evolution operators. Proceedings of the International Conference on Intelligent Agent Technology (IAT-2004), IEEE Computer Science Press, Los Alamitos, CA. 2004.

  • D. Qi and R. Sun, Integrating reinforcement learning, bidding and genetic algorithms. Proceedings of the International Conference on Intelligent Agent Technology (IAT-2003), Halifax, Canada. IEEE Compute Science Press. 2003.

  • R. Sun, Beyond simple rule extraction: the extraction of planning knowledge from reinforcement learners. Proceedings of the International Joint Conference on Neural Networks, Como, Italy. July 24-27, 2000. IEEE Press, Piscataway, NJ.

  • R. Sun and T. Peterson, Automatic partitioning for multi-agent reinforcement learning. From Animals to Animats: Proceedings of the International Conference of Simulation of Adaptive Behavior (SAB'2000). Paris, France. MIT Press, Cambridge, MA. 2000.

  • R. Sun and C. Sessions, Self segmentation of sequences. Proceedings of International Joint Conference on Neural Networks, Washington, DC. July 10-15, 1999. IEEE Press, Piscataway, NJ.

  • R. Sun, Supplementing neural reinforcement learning with symbolic methods: Possibilities and challenges. Proceedings of International Joint Conference on Neural Networks, Washington, DC. July 10-15, 1999. IEEE Press, Piscataway, NJ.

  • R. Sun, Knowledge extraction from reinforcement learning. Proceedings of International Joint Conference on Neural Networks, Washington, DC. July 10-15, 1999. IEEE Press, Piscataway, NJ.

  • R. Sun and C. Sessions, Extracting plans from reinforcement learners. Proceedings of the 1998 International Symposium on Intelligent Data Engineering and Learning, October, 1998. Springer-Verlag.

  • R. Sun and C. Sessions, Learning to plan probabilistically from neural networks. Proceedings of IEEE International Conference on Neural Networks, Anchorage, Alaska. May 4-9, 1998. IEEE Press, Piscataway, NJ.

  • R. Sun and T. Peterson, Automatic partitioning for multi-agent reinforcement learning. Proceedings of International Conference on Neural Information Processing (ICONIP'98). KitaKyushu, Japan. October, 1998.

  • T. Peterson and R. Sun, An RBF network alternative to a hybrid architecture. Proceedings of IEEE International Conference on Neural Networks, Anchorage, Alaska. May 4-9, 1998. IEEE Press, Piscataway, NJ.

  • R. Sun and T. Peterson, A hybrid model for learning sequential navigation. Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation. Monterey, CA. IEEE Press. 1997.

  • R. Sun and T. Peterson, A hybrid model for learning sequential decision making. Proceedings of Joint Conference on Information Sciences. pp.147-152. Research Triangle Park, NC. March, 1997.

  • R. Sun, T. Peterson, and E. Merrill, A hybrid architecture for learning reactive sequential decision making. Proceedings of AAAI Fall Symposium on Learning Complex Behavior in Adaptive Intelligent Systems. Cambridge, MA. Fall, 1996.

  • R. Sun and T. Peterson, A hybrid connectionist architecture for sequntial decision making. In: R. Sun and F. Alexandre, (eds.) The Working Notes of the IJCAI Workshop on Connectionist-Symbolic Integration. 1995.