Abstract
Paul MacLean, following the evolutionary scheme, proposed the idea of “triune—brain,” in which the cortex is organised into three layers. He proposed that the three layers are responsible for instinctual behaviour, the motivational and emotional influences, and the rational influences on decision making, respectively. We borrow this metaphor of triune-brain to propose a unifying viewpoint for bringing together disparate themes of intelligent computation. In this framework, quantitative methods of statistics are the equivalent of behaviours at the instinctual layer, rule-based approaches of the symbol processing—kind, being rational and logical, sit at the top and methods of soft computing (neural networks, fuzzy logic, genetic algorithms, etc.) operate at the intermediate level. It is argued that just as all the levels are important for a functioning organism, this three-level interaction is crucial for theories of intelligent computation.
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
Matarazzo, J. D., 1972, Wechsler’s measurement and appraisal of adult intelligence (Fifth edition), Oxford University Press, New York, NY.
Gardner, H., 1993, Frames of mind: The theory of multiple intelligences (Second edition), Fontana Press, Harper Collins Publishers, London.
Hunt, E., 1995, The role of intelligence in modern society, American Scientist, 83, 356–368.
Newell, A., 1990, Unified theories of cognition, Harvard University Press, Cambridge, MA.
Fodor, J. A., 1976, The language of thought, Harvester Press (Harvard University Press paperback), Sussex, UK.
West, D. M., and Travis, L. E., 1991, The computational metaphor and artificial intelligence: A reflective examination of a theoretical falsework, AI Magazine, 12(1), 64–79.
Honavar, V., and Uhr, L., 1994, Artificial intelligence and neural networks: Steps toward principled integration, Academic Press, Boston, MA.
Bapi, R. S., McCabe, S. L., and Roy, R., 1996, Book Review of Artificial intelligence and neural networks: Steps toward principled integration, V. Honavar and L. Uhr (Eds.), 1994, Academic Press, Boston, MA, Neural Networks, 9(3), 545–548.
Hamad, S., 1990, The symbol grounding problem, Physica D, 42, 335–346.
Roy, R., and Bapi, R. S., 1996, AI at the cross-roads: Past achievements and future challenges, Book review of Artificial Intelligence in Perspective, D. Bobrow (Ed.), 1993, SIGART Bulletin, 7(1), 10–13.
Jantsch, E., 1980, The self-organizing universe: Scientific and human implications of the emerging paradigm of evolution, Pergamon Press, Oxford.
Maturana, H. R., and Varela, F. J., 1992, The tree of knowledge: The biological roots of human understanding (Rev. ed.), Shambala.
West, D. M., and Travis, L. E., 1991, From society to landscape: Alternative metaphors for artificial intelligence, AI Magazine, 12(2), 69–83.
Langton, C. G. et al., 1991, Artificial Life II, Addison-Wesley Publishing Co.
Briggs, J. P., and Peat, F. D., 1984, Looking glass universe: The emerging science of wholeness, Fontana Paperbacks, Harper Collins Publishers, London.
Pollock, J. B., 1993, On wings of knowledge: A review of Allen Newell’s Unified theories of cognition, Artificial Intelligence, 59, 355–369.
MacLean, P. D., 1990, The triune brain in evolution, Plenum Press, New York, NY.
Bapi, R. S. and Denham, R. S., 1996, Computational Intelligence: A Synergistic Viewpoint, International Journal of Computational Intelligence and Organizations, 1, 2–9.
Leven, S. J., 1987, Choice and Neural Process, Unpublished doctoral dissertation, University of Texas at Arlington, Arlington, TX.
Raghupathi, W., Levine, D. S., Bapi, R. S., and Schkade, L. L., 1994, Toward connectionist representation of legal knowledge, In D. S. Levine and M. Aparicio IV (Eds.), Neural networks for knowledge representation and inference, Lawrence Erlbaum Associates, Hillsdale, NJ, pp. 269–282.
Levine, D. S., and Leven, S. J., 1992, Motivation, emotion, and goal direction in neural networks, Lawrence Erlbaum Associates, Hillsdale, NJ.
Bapi, R. S., 1996, Exploring the role of emotion in the design of autonomous systems, In M. van der Heyden, J. Mrsic-Flögel, and K. Weigl (Eds.), Proceedings of the Helsinki Neural Network Group Workshop HELNET95, Vacanciel, France, Oct 4–7, 1995, VU University Press, Amsterdam, pp. 115–125.
Leven, S. J., 1992, Learned helplessness, memory, and the dynamics of hope, In D. S. Levine and S. J. Leven (Eds.), Motivation, emotion, and goal direction in neural networks, Lawrence Erlbaum Associates, Hillsdale, NJ, pp. 259–299.
Omlin, C. W., and Giles, C. L., 1996, Extraction of rules from discrete-time recurrent neural networks, Neural Networks, 9(1), 41–52.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer-Verlag London
About this paper
Cite this paper
Bapi, R.S. (1998). Triune-Brain Inspired Unifying View of Intelligent Computation. In: Chawdhry, P.K., Roy, R., Pant, R.K. (eds) Soft Computing in Engineering Design and Manufacturing. Springer, London. https://doi.org/10.1007/978-1-4471-0427-8_3
Download citation
DOI: https://doi.org/10.1007/978-1-4471-0427-8_3
Publisher Name: Springer, London
Print ISBN: 978-3-540-76214-0
Online ISBN: 978-1-4471-0427-8
eBook Packages: Springer Book Archive