Turing was an exceptional mathematician with a peculiar and fascinating personality and yet he remains largely unknown. In fact, he might be considered the father of the von Neumann architecture computer and the pioneer of Artificial Intelligence. And all thanks to his machines; both those that Church called “Turing machines” and the a-, c-, o-, unorganized- and p-machines, which gave rise to evolutionary computations and genetic programming as well as connectionism and learning. This paper looks at all of these and (...) at why he is such an often overlooked and misunderstood figure. (shrink)

Very few scientists today question the fact that information, together with matter and energy, is one of the three constructs forming the ontology of the universe. However, there is still a long way to go before in order to establish the interrelations between information and energy and information and matter, as Einstein did between matter and energy. In this paper, after introducing the energy, matter, information model, which covers the three constructs and their relationships, we illustrate real examples—two qualitative and (...) two quantitative—of the interrelations between energy and information. This closes the open question with respect to the interrelationship between energy and information. (shrink)

In the centenary year of Turing’s birth, a lot of good things are sure to be written about him. But it is hard to find something new to write about Turing. This is the biggest merit of this article: it shows how von Neumann’s architecture of the modern computer is a serendipitous consequence of the universal Turing machine, built to solve a logical problem.

The state of computing science and, particularly, software engineering and knowledge engineering is generally considered immature. The best starting point for achieving a mature engineering discipline is a solid scientific theory, and the primary reason behind the immaturity in these fields is precisely that computing science still has no such agreed upon underlying theory. As theories in other fields of science do, this paper formally establishes the fundamental elements and postulates making up a first attempt at a theory in this (...) field, considering the features and peculiarities of computing science. The fundamental elements of this approach are informons and holons, and it is a general and comprehensive theory of software engineering and knowledge engineering that related disciplines (e.g., information systems) can particularise and/or extend to take benefit from it (Lakatos’ concepts of core theory and protective belt theories). (shrink)

Gottfried Wilhelm Leibniz is the self-proclaimed inventor of the binary system and is considered as such by most historians of mathematics and/or mathematicians. Really though, we owe the groundwork of today’s computing not to Leibniz but to the Englishman Thomas Harriot and the Spaniard Juan Caramuel de Lobkowitz, whom Leibniz plagiarized. This plagiarism has been identified on the basis of several facts: Caramuel’s work on the binary system is earlier than Leibniz’s, Leibniz was acquainted—both directly and indirectly—with Caramuel’s work and (...) Leibniz had a natural tendency to plagiarize scientific works. (shrink)

In this paper we present a paradigmatic example of the use in knowledge management of techniques from other fields, namely mathematical analysis. We also highlight that the Jacobi method presented here takes precedence over the better known Hungarian method. Finally, we signify that the Jacobi method represents the first known or recognized case of serendipity in both knowledge management and operational research. This paper thus demonstrates the intersection between knowledge management, mathematical analysis and operational research and how taking historical perspectives (...) are important for recognising future applications of knowledge management. This results in a better understanding of knowledge management and how it can be applied in the future. It has been shown how knowledge management relates to historical mathematical principles. (shrink)