A model of the development of the information sciences is described and used to account for past events and predict future trends, particularly fifth and sixth generation priorities. The information sciences came into prominence as electronic device technology enabled the social need to cope with an increasingly complex world to be satisfied. Underlying all developments in computing is a tiered succession of learning curves which make up the infrastructure of the computing industry. The paper provides a framework for the information sciences based on this logical progression of developments. It links this empirically to key events in the development of computing. It links it theoretically to a model of economic, social, scientific and individual development as related learning processes with a simple phenomenological model. The fifth generation development program with its emphasis on human-computer interaction and artificial intelligence, and the sixth generation research program with...

System-theoretic accounts of the epistemological processes underlying knowledge acquisition have been shown to apply to both individual human behavior and social development processes, and to enable algorithms to be developed for computer-based systems modeling. Such accounts are applicable to the upper levels of the hierarchy of autonomous systems to provide models of socio-economic behavior. In this paper they are applied to the development of information technology, and used to account for past events and predict future trends in relevant industries such as computing and genetic engineering. Underlying all developments in information technology is a tiered succession of learning curves which make up the infrastructure of the relevant industries. The paper provides a framework for the industries based on this logical progression of developments. It links this empirically to key events in the development of computing and genetic engineering. It links it theoretically to a model of eco...

this article nevertheless uses the colloquial version of the term von Neumann computer to refer to any computer with the fundamental characteristics described in Section 3. The term "Princeton architecture" is then used to distinguish between computers with the split (Harvard) and unified (Princeton) memory organizations

A course in discrete mathematics is a relatively recent addition, within the last 30 or 40 years, to the modern American undergraduate curriculum, born out of a need to instruct computer science majors in algorithmic thought. The roots of discrete mathematics, however, are as old as mathematics itself, with the notion of counting a discrete operation, usually cited as the first mathematical development

We describe the computer which was defined in von Neumann’s unpublished

26 February 2005: A clarification has been provided in Section 4.2 in order to explain the “inhibitor ” symbol used in the inverter. The reference above to the published copy of this paper was corrected(!). And, since after this paper was published the edited “First Draft Report on the EDVAC ” was published, a reference to this publication is provided in [1]. 15 June 2006: The date of publication of the Weik Report [9] was corrected from 1951 to 1955.