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.