The progress of natural sciences and technology is closely related to quantitative research work. Its methodology is well established and can be described as follows: An object or phenomenon of interest is first quantitatively explored by various measurements and then the experimental results are represented in terms of empirical relations which may subsequently be analytically described in terms of physical laws. The research work in various fields of natural sciences and technology is performed by scientists, utilizing similar experimental techniques and information processing methods. Therefore, a question arises whether it might be possible to develop a general type of machine that could perform such work autonomously, analogous to robots that do mechanical work on industrial production lines. In order to be able to design such a machine, the general procedures of quantitative research work must first be formalized so that such work can be described as a process similar to that which might be used as an industrial test procedure. And then, this process must be implemented using an appropriate technique.
KeywordsInformation Processing System Natural Phenomenon Empirical Information Intelligent Controller Quantitative Science
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- 1.The Handbook of Artificial Intelligence, ed. by A. Barr, P. R. Cohen, and E. A. Feigenbaum (Addison-Wesley Publ. Co., Reading, MA 1989)Google Scholar
- 2.Self-Organization and Life: From Simple Rules to Global Complexity, Proc. Int. Conf. ECAL’93 (Center for Non-Linear Phenomena and Complex Systems, CP 231, Université Libre de Bruxelles, Brussels 1993)Google Scholar
- 7.S. A. Kauffman: The Origins of Order, Self-Organization and Selection in Evolution (Oxford University Press, New York 1993 )Google Scholar
- 8.T. Kohonen: Self-Organization and Associative Memory ( Springer, Berlin 1989 )Google Scholar
- 10.D. E. Rumelhart, J. L. McClelland, and PDP Research Group: Parallel Distributed Processing, Explorations in Microstructure of Cognition ( MIT Press, Cambridge, MA 1988 )Google Scholar
- 11.Handbook of Intelligent Control: Neural, Fuzzy, and Adaptive Approaches, ed. by A. White, D. A. Sofge (Van Nostrand Reinhold, New York 1992)Google Scholar