Summary. This paper addresses the different models and their functions in cognitive science. First, this paper discusses the various uses and meanings of various models in science and two kinds of functions of each model such as idealizations and representations of the real world. In cognitive science, cognitive architectures were used as cognitive models. Second, this paper discusses Neil Stillings’ global cognitive architecture as well as an example. In addition, this paper focuses on several forms of cognitive models including the von Neumann model, symbol system model and production system model. Further, it was argued that the connectionist model was a better approach to understanding the mechanisms of human cognition through the use of simulated networks of simple, neuron-like processing units. Finally, four models in neuroscience were addressed, being: different models of sensory processing, Marshall-Newcombe’s symbolic model of reading, model of memory system, and Mishkin-Appenzeller’s model of visual memory functions. These models are approaches to physical implementation, not a computational approach to cognition.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anderson, J.R.: The Architecture of Cognition. Harvard University Press, Cambridge, MA (1983)
Anderson, J.R.: The Adaptive Character of Thought. Erlbaum, Hillsdale, NJ (1993a)
Anderson, J.R.: Rules of Mind. Erlbaum, Hillsdale, NJ (1993b)
Atkinson, R.C., Shiffrin, R.M.: Human memory: a proposed system and its control processes. In K.W. Spence and J.T. Spence, eds., Psychology of Learning and Motivation II. Academic Press, New York (1968)
Baddeley, A.: Human Memory: Theory and Practice. Allyn & Bacon, Boston MA and London (1998)
Broadbent, D.E.: Perception and Communication. Pergamon, Oxford (1958)
Dawson, M.R.W.: Minds and Machines: Connectionism and Psychological Modeling. Blackwell Publishing Ltd (2004)
Giere, R.N.: Using models to represent reality. In L. Magnani, N.J. Nersessian, and P. Thagard, eds., Model-Based Reasoning in Scientific Discovery. Kluwer Academic/Plenum Publishers, New York (1999) 41-58
Harré, R.: Cognitive Science: a Philosophical Introduction. SAGE, London (2002)
Just, M.A., Carpenter, P.A.: A capacity theory of comprehension: individual differences in working memory. Psychological Review 99 (1992) 122-149
Marshall, J.C., Newcombe, F.: Lexical access: a perspective from pathology. Cognition 10 (1981) 209-214
McClelland, J.L.: Retrieving general and specific information from stored knowledge of specifics. Proceedings of the Third Annual Conference of the Cog-nitive Science Society, Berkeley, CA (1981) 170-172
McClelland, J.L., Rumellhart, D.E.: An interactive activation model of context effects in letter perception: part1: an account of basic findings. Psychological Review 88 (1981) 375-407
McLeod, P., Plunkett, K., Rolls, E.T.: Introduction to Connectionist Modeling of Cognitive Processes. Oxford University Press, Oxford (1998)
Meyer, D.E., Kieras, D.E.: A computational theory of executive cognitive processes and multiple-task performance: Part1: basic mechanism. Psychologi-cal Review 104 (1997) 3-65
Minsky, M.A.: Framework for representing knowledge. In: P. Winston, ed., The Psychology of Computer Vision. McGraw-Hill, New York (1975)
Mishkin, M., Appenzeller, T.: The anatomy of memory. Scientific American 256 (1987) 80-89
Mitchell, T.M., Utgoff, P.E., and Banerji, R.: Learning by experimenta-tion: Acquiring and refining problem-solving heuristics. In Michalski, R.S., Carbonell, J., and Mitchell, T.M. eds., Machine Learning: An Artificial Intelli-gence Approach. vol1. Tioga, Palo Alto, Calif (1983)
Nersessian, N.J.: Model-based reasoning in conceptual change. In L. Magnani, N.J. Nersessian, P. Thagard, eds., Model-Based Reasoning in Scientific Discovery. Kluwer Academic/Plenum Publishers, New York (1999), pp5-22
Newell, A.: Unified Theories of Cognition. Harvard University Press, Cambridge, MA (1990)
Newell, A., Simon, H.A.: The simulation of human thought. Current Trends in Psychological Theory. Pittsburgh University Press, Pittsburgh PA (1961)
Newell, A., Simon, H.A.: Human Problem Solving. Prentice Hall, Englewood Cliffs, NF (1972)
Newell, A., Simon, H.A.: Computer science as empirical inquiry: symbols and search. Communications of the ACM 19 (1976) 113-126
Newell, A., Simon, H.A., Shaw, J.C.: Elements of a theory of human problem solving. Psychological Review 65 (1958) 151-166
Pinel, J.P.J.: Biopsychology. Allyn and Bacon, Boston (1990)
Rumelhart, D.E., Ortony, A.: The representation of knowledge in memory. In R.C. Anderson et al., eds., Schooling and the Acquisition of Knowledge. Erlbaum, Hillsdale, NJ (1976)
Rumelhart, D.E., McClelland, J.L.: On learning the past tenses of English verbs. In J.L. McClelland, D.E. Rumelhart, and the PDP Research Group, eds., Paral-lel Distributed Processing: explorations in the microstructure of cognition, vol.2. MIT Press, Cambridge, MA (1986) 216-271
Rolls, E.C.: The representation and storage of information in neural networks in the primate cerebral cortex and hippocampus. In R. Durbin, C. Miall, and G. Mitchison, eds., The Computing Neuron. Addison-Wesley, Reading MA (1989)
Sejnowski, T.J., Rosenberg, C.R.: Parallel networks that learn to pronounce English text. Complex Systems 1 (1987) 145-168
Schank, R.C., Abelson, R.: Scripts, Plans, Goals and Understanding. Erlbaum, Hillsdale, NJ (1977)
Sloman, S.A.: The empirical case for two systems of reasoning. Psychological Bulletin 119 (1996) 3-22
Smolensky, P.: On the proper treatment of connectionism. Behavioral and Brain Science 11 (1988) 1-74
Squire, L.R.: Memory and Brain. Oxford University Press, New York (1987)
Stillings, N.A. et al.: Cognitive Science: an introduction, second edition. MIT Press, Cambridge, Mass (1995)
Wang, H.T., Mathur, B., Kock, K.: I thought I saw it move: computing optical flow in the primate visual system. In M.A. Gluck and D.E. Rumelhart, eds., Neuroscience and Connectionist Theory. Erlbaum, Hillsdale, NJ (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Wei, Yd. (2007). Model-Based Reasoning in Cognitive Science. In: Magnani, L., Li, P. (eds) Model-Based Reasoning in Science, Technology, and Medicine. Studies in Computational Intelligence, vol 64. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71986-1_16
Download citation
DOI: https://doi.org/10.1007/978-3-540-71986-1_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71985-4
Online ISBN: 978-3-540-71986-1
eBook Packages: EngineeringEngineering (R0)