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In a previous paper (Gaines, 1978) on progress in general systems research... I avoided the issue of defining a system. I noted that no definitions a… - Brian R. Gaines
" "In a previous paper (Gaines, 1978) on progress in general systems research... I avoided the issue of defining a system. I noted that no definitions are satisfactory, and it seemed to me the essence of the subject area that none can be so. I went on to say that it is the systems approach—emphasizing lack of disciplinary boundaries, the freedom to apply knowledge, and techniques gathered in one field to problems in another, or to suggest that two distinct fields are in fact one, the disciplined freedom of the unconstrained intellect—that has been the source of dynamism and progress. I noted that perhaps the most telling progress of all is that we can so confidently speak of a common field of interest knowing that we could not, and would not wish to, agree on a definition of what a system is.
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About Brian R. Gaines
Brian R. Gaines (born circa 1938) is a British scientist, engineer, and Professor Emeritus Killam Memorial Research Professor and Director of the Knowledge Science Institute at the University of Calgary.
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Additional quotes by Brian R. Gaines
s have long provided visual languages widely used in many different disciplines and application domains. Abstractly, they are sorted graphs visually represented as nodes having a type, name and content, some of which are linked by arcs. Concretely, they are structured diagrams having discipline- and domain-specific interpretations for their user communities, and, sometimes, formally defining computer data structures. Concept maps have been used for a wide range of purposes and it would be useful to make such usage available over the World Wide Web.
Tracking the individual learning curves of the major technologies that comprise the infrastructure of information technology provides a more detailed account of the present and future state-of-the art of the technologies underlying convergence. The base technologies of digital electronics, general-purpose computer architectures, software and interaction are mature and provide solid foundations for computer science. The upper technologies of knowledge representation and acquisition, autonomy and sociality, support product innovation and provide the beginnings of foundations for knowledge science. Well's dream of a world brain making available all of human knowledge is well on its way to realization and it is in the representation, acquisition, and access and effective application of that knowledge that the commercial potential and socio-economic impact of convergence lies.
The postulation of a principle of causality, “to every effect there is a cause,” has been a continuing central problem for philosophy (Popper, 1972). Its role as a source of contention in modern science (Jauch, 1973) is epitomized by Einstein’s remark that, “I can’t believe that God plays dice.” Many of the arguments about the application of the principle are very relevant to systems science and to problems of system identification and machine learning, on the one hand,and to epistemology and behavioural psychology, on the other. In current system science the theory of causal deterministic systems is most well developed and generally applied, while the theory of modeling with alternative structures, e.g., stochastic automata, indeterminate automata, products of asynchronous automata, etc., has not been developed to the same degree.
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