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Mon Jun 5 16:42:55 EDT 2006


Ron Sun
Edward Merrill
Todd Peterson

To appear in: Cognitive Science.

http://www.cecs,missouri.edu/~rsun/sun.CS99.ps

ABSTRACT
This paper  presents a skill learning model {\sc Clarion}.  Different from
existing models of mostly high-level skill learning that use a top-down
approach (that is, turning declarative knowledge into procedural knowledge
through practice), we adopt a bottom-up approach toward low-level skill 
learning, where procedural knowledge develops first and
declarative knowledge develops later.  Our model is formed
by integrating connectionist, reinforcement, and symbolic learning
methods to perform on-line reactive learning.
It adopts a two-level dual-representation framework
(Sun 1995), with a combination of localist and distributed representation.
We compare the model with human data in a minefield navigation task,
demonstrating some  match between the model and human data in several
respects.




Two papers on accounting for consciousness computationally:
--------------------------------------------------
Accounting for the Computational Basis of Consciousness: A Connectionist
Approach

Ron Sun

To appear in: Consciousness and Cognition, 1999.

http://www.cecs.missouri.edu/~rsun/sun.CC99.ps

ABSTRACT
This paper argues for an explanation of the mechanistic (computational) 
basis of consciousness that is based on the
distinction between localist (symbolic) representation and
distributed representation, the ideas of which have been put forth in
the connectionist literature.
A model is developed to substantiate and test this approach.
The paper also explores the issue of the functional roles of consciousness,
in relation to the proposed mechanistic explanation of consciousness.
The model,  embodying the representational difference, is able
to account for the functional role of consciousness,
in the form of the synergy between the conscious and the unconscious.
The fit between the model and various cognitive phenomena and data
(documented in the psychological literatures) is discussed to 
accentuate the plausibility of the model and its explanation of 
consciousness.  Comparisons with existing models of consciousness are made
in the end.


--------------------------------------------------
Learning, Action,  and Consciousness: A Hybrid Approach
toward  Modeling Consciousness

Ron Sun

Appeared in: Neural Networks, 10 (7), pp.1317-1331. 1997.

http://www.cecs.missouri.edu/~rsun/sun.nn97.ps

ABSTRACT
This paper is an attempt at understanding the issue of consciousness
through investigating its functional role, especially in learning,
and through devising hybrid neural network models that
(in a qualitative manner) approximate characteristics of human 
consciousness.  In so doing, the paper examines explicit and implicit 
learning in a variety of psychological experiments
and delineates the conscious/unconscious distinction in
terms of the two types of learning and their respective products.
The distinctions are captured in a two-level action-based 
model {\sc Clarion}.  Some fundamental theoretical issues are also
clarified with the help of the model.
Comparisons with existing models of consciousness are made
to accentuate the present  approach.






Finally,  a paper on computational analysis of the model:
---------------------------------
Autonomous Learning of Sequential Tasks: Experiments and Analyses

by Ron Sun, Todd Peterson

Appeared in:  IEEE Transactions on Neural Networks, Vol.9, No.6, pp.1217-1234.  November, 1998.

http://www.cecs.missouri.edu/~rsun/sun.tnn98.ps

ABSTRACT:
This paper presents  a novel learning model {\sc Clarion}, which is a hybrid 
model based on the two-level approach proposed in Sun (1995).
The model integrates neural, reinforcement, and symbolic learning 
methods to perform on-line,  bottom-up learning (i.e.,
learning that goes from neural to symbolic representations).
The model utilizes both procedural and declarative knowledge
(in neural and symbolic representations respectively),
tapping into the  synergy of the two types of processes.
It was applied to deal with sequential decision tasks.
Experiments and analyses  in various ways
are reported that shed light on the advantages of the model.


===========================================================================
Prof. Ron Sun                           http://www.cecs.missouri.edu/~rsun
CECS Department                         phone: (573) 884-7662
University of Missouri-Columbia         fax:   (573) 882 8318 
201 Engineering Building West
Columbia, MO 65211-2060                 email: rsun at cecs.missouri.edu 

http://www.cecs.missouri.edu/~rsun
http://www.cecs.missouri.edu/~rsun/journal.html
http://www.cecs.missouri.edu/~rsun/clarion.html
===========================================================================





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