List of publications on CLARION
-- Quick sketches of the cognitive architecture
R. Sun,
The CLARION cognitive architecture:
Extending cognitive modeling to social simulation
In: Ron Sun (ed.), Cognition and Multi-Agent Interaction.
Cambridge University Press, New York. 2006.
R. Sun,
The motivational and metacognitive control in CLARION.
In: W. Gray (ed.),
Modeling Integrated Cognitive Systems.
Oxford University Press, New York. 2007.
R. Sun, T. Peterson, and C. Sessions,
Beyond simple rule extraction: acquiring planning knowledge from neural networks.
Proceedings of WIRN'01, Salermo, Italy. Springer-Verlag, 2001.
[
PDF]
-- Detailed information about the cognitive architecture
R. Sun,
A Detailed Specification of CLARION 5.0
.
Technical report. 2003.
(It contains detailed technical specifications of
CLARION 5.0.)
Addendum 1:
The enhanced description of the motivational subsystem.
Addendum 2:
The enhanced description of similarity-based reasoning.
Addendum 3:
The properties of the CLARION-H implementation.
Addendum 4:
Q and A.
A much simplified description of CLARION 5.0, written by a student
as a project report (which only provides some general ideas):
A Simplified Introduction to CLARION 5.0
.
Technical report. 2004.
For details of cognitive modeling, see the following papers:
-- Cognitive modeling using CLARION
R. Sun,
Moral judgment, human motivation, and neural networks.
Cognitive Computation, in press.
R. Sun,
Autonomous generation of symbolic representations through subsymbolic activities.
Philosophical Psychology, in press.
R. Sun and S. Helie,
Psychologically realistic cognitive agents: Taking human cognition seriously. Journal of Experimental and Theoretical Artificial Intelligence, in press.
R. Sun and P. Fleischer,
A cognitive social simulation of tribal survival strategies: The importance of cognitive and motivational factors. Journal of Cognition and Culture, in press.
R. Sun and R. Mathews,
Implicit cognition, emotion, and meta-cognitive control.
Mind and Society, the special issue on Dual Processes Theories of Language and Thinking, Vol.11, No.1, pp.107-119. 2012.
R. Sun,
Memory Systems within a Cognitive Architecture.
New Ideas in Psychology, Vol.30, pp.227-240. 2012.
R. Sun, N. Wilson, and R. Mathews,
Accounting for certain mental disorders within a comprehensive cognitive architecture.
Cognitive Computation, Vol.3, No.2, pp.341-359. 2011.
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.
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,
Motivational representations within a computational cognitive architecture
.
Cognitive Computation,
Vol.1, No.1, pp.91-103. 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.
R. Sun and I. Naveh,
Social institution, cognition, and survival:
A cognitive-social simulation
.
Mind and Society, Vol.6, No.2, pp.115-142. 2007.
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, 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]
R. Sun,
The importance of cognitive architectures: An analysis based on CLARION.
Journal of Experimental and Theoretical Artificial Intelligence, Vol.19, No.2, p
p.159-193.
2007
R. Sun and X. Zhang,
Accounting for a variety of reasoning
data within a cognitive architecture.
Journal of Experimental and Theoretical Artificial Intelligence,
Vol.18, No.2, pp.169-191. 2006.
R. Sun, X. Zhang, and R. Mathews,
Modeling meta-cognition in a cognitive architecture.
Cognitive Systems Research, Vol.7, No.4, pp.327-338. 2006.
[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 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]
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
]
L. A. Coward and R. Sun,
Criteria for an effective theory of consciousness and
some preliminary attempts.
Consciousness and Cognition, Vol.13, pp. 268-301.
2004.
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,
E. Merrill, and T. Peterson,
Knowledge acquisition via bottom-up skill learning.
Knowledge Engineering: Systems, Techniques and Applications,
ed. C. Leondes, Academic Press. 2000.
R. Sun,
Accounting for the computational basis of consciousness: A connectionist
approach.
Consciousness and Cognition, Vol.8,
pp.529-565. December, 1999.
[
PDF]
R. Sun,
Learning, action, and consciousness: A hybrid approach towards modeling
consciousness.
Neural Networks, special issue on consciousness.
10 (7), pp.1317-1331. 1997.
(an overview)
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, X. Zhang, and R. Mathews,
Modeling meta-cognition in a cognitive architecture.
Proceedings of the 27th Annual
Conference of the Cognitive Science Society, Stresa, Italy.
Lawrence Erlbaum Associates, Mahwah, NJ. 2005.
R. Sun and X. Zhang,
Accounting for similarity-based reasoning within a cognitive architecture.
Proceedings of the 26th Annual
Conference of the Cognitive Science Society, Chicago.
Lawrence Erlbaum Associates, Mahwah, NJ. 2004.
R. Sun and X. Zhang,
Accounting for discovery in a cognitive architecture.
Proceedings of the 25th Annual Conference of the Cognitive Science Society,
Boston, MA.
Lawrence Erlbaum Associates, Mahwah, NJ.
2003.
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.
Proc. 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.
Proc. of The Second European Conference on Cognitive Modeling, Nottingham,
UK.
April, 1998.
For model details, see the following papers:
-- CLARION 3.0
R. Sun and T. Peterson,
Autonomous learning
of sequential tasks:
experiments and analyses.
IEEE Transaction on Neural Networks,
November, 1998.
R. Sun and T. Peterson,
A subsymbolic+symbolic model for learning sequential navigation.
Proc. of the Fifth International
Conference of the Society for Adaptive Behavior (SAB'98).
Zurich, Switzerland. 1998.
MIT Press.
-- CLARION 2.0 and 1.0
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,
Some experiments with a hybrid model
for learning sequential decision making.
Information Sciences. Vol.111, pp.83-107.
R. Sun and T. Peterson,
A hybrid model for learning sequential navigation.
Proc. of IEEE International Symposium on Computational Intelligence
in Robotics and Automation.
Monterey, CA. IEEE Press. 1997.
R. Sun, T. Peterson, and E. Merrill,
Bottom-up skill learning in reactive sequential decision tasks.
Proc.of 18th Cognitive Science Society Conference,
Lawrence Erlbaum Associates, Hillsdale, NJ.
pp.684-690. 1996.
-- CLARION-RBF
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.
-- Plan extraction
R. Sun
and C. Sessions,
Learning plans without a priori knowledge.
Adaptive Behavior,
Vol.8, Issue 3/4, 2000.
[formatted
PDF]
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.
-- Partitioning (modular reinforcement learning)
R. Sun and T. Peterson,
Multi-agent reinforcement learning: weighting and partitioning.
Neural Networks,
1999.
[Elsevier-formatted
PDF]
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.
-- Segmentation
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,
in press.
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.
-- Additional Publications
For additional publications on CLARION, see
Prof. Ron Sun's home page .
See also the consciousness page.
See also the
theoretical work on computational cognitive modeling
page.