FYI: Cognitive Modeling, Linguasphere Register
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Ron Sun
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Announcing four papers on cognitive modeling and cognitive architectures based on hybrid reinforcement learning methods --- the CLARION model: A paper on cognitive modeling using CLARION: - ------------------------------------------------ >From Implicit Skills to Explicit Knowledge: A Bottom-Up Model of Skill Learning 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 Connectionis 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 tha (in a qualitative manner) approximate characteristics of human consciousness. In so doing, the paper examines explicit and implici 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 Wes Columbia, MO 65211-2060 email: rsun@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 =========================================================================== |
