Brian R. Gaines

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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.


  • Concept maps 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.

Foundations of fuzzy reasoning (1976)

Gaines (1976) "Foundations of fuzzy reasoning", in: International Journal of Man-Machine Studies 8(6), 623-668, 1976.
  • Models of human reasoning are clearly relevant to a wide variety of subject areas such as sociology, economics, psychology, artificial intelligence and man-machine systems. Broadly there are two types: psychological models of what people actually do; and formal models of what logicians and philosophers feel a rational individual would, or should, do. The main problem with the former is that it is extremely difficult to monitor thought processes - the behaviourist approach is perhaps reasonable with rats but a ridiculously inadequate source of data on man - the introspectionist approach is far more successful [e.g. in analysing human chess strategy... but the data obtained is still incomplete and may not reflect the actual thought processes involved.
    • p. 623.

On the Complexity of Causal Models (1977)

Gaines (1976) "On the Complexity of Causal Models" in: International Journal of General Systems, 1977.
  • Principle of causality is fundamental to human thinking, and it has been observed experimentally that this assumption leads to complex hypothesis formation by human subjects attempting to solve comparatively simple problems involving a causal randomly generated events
    • Introduction.
  • 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.
    • Introduction.

General systems research: quo vadis? (1979)

Gaines (1979) "General systems research: quo vadis?", General Systems: Yearbook of the Society for General Systems Research, Vol. 24 (1979), p. 1-9.
  • 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.
    • Gaines is referring here to his 1978 article "Progress in general systems research". In Klir, G. J. (ed.), Applied General Systems Research, New York: Plenum Press, 1978, pp. 3-28.

Convergence to the Information Highway (1996)

Gaines (1996) "Convergence to the Information Highway" on July 16, 1996.
  • The motivation for an "information highway" was expressed in 1937, just prior to the advent of computer technology, when Wells was promoting the concept of a "World Brain" based on a "permanent world encyclopaedia" as a social good through giving universal access to all of human knowledge. He remarks:

    "our contemporary encyclopaedias are still in the coach-and-horses phase of development, rather than in the phase of the automobile and the aeroplane. Encyclopaedic enterprise has not kept pace with material progress. These observers realize that the modern facilities of transport, radio, photographic reproduction and so forth are rendering practicable a much more fully succinct and accessible assembly of facts and ideas than was ever possible before." (Wells, 1938)

    • First paragraph
  • Bush, a technical advisor to Roosevelt, published in 1945 an article in Atlantic Monthly which highlighted problems in the growth of knowledge, and proposed a technological solution based on his concept of memex, a multimedia personal computer:

    "Professionally, our methods of transmitting and reviewing the results of research are generations old and by now are totally inadequate for their purpose...The difficulty seems to be not so much that we publish unduly in view of the extent and variety of present-day interests, but rather that publication has been extended far beyond our present ability to make real use of the record." (Bush, 1945)

    The world brain has continued for over fifty years to provide an active objective for the information systems community (Goodman, 1987), and memex is often quoted as having been realized fifty years later through the World Wide Web (Berners-Lee, Cailliau, Luotonen, Nielsen and Secret, 1994).
    • First paragraph
  • 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.
    • Last paragraph
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