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      What are models of high-level computation (MHCs)?Accordingly, plenty of Models of High-Level Computation (MHCs) have been proposed over the last half century so as to capture the essence of complex computations. In this paper, we describe the meaning, key properties, current paradigms and future directions of MHCs. The rest of the paper is structured as follows.

      Models of High-Level Computation - arXiv.org

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      Should we confuse high-level and higher-order computability?1We should not confuse high-level with higher-order computations . Higher-order computability is a well-established field in theoretical computer science, whose aim is to study computations that receive and produce other computations. As individual devices are treated as modular black boxes, their internal details are irrelevant.

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      What is a classical model of computation?Classical models of computation formally emerged during the first half of the century 20th, as an attempt to capture the very essence of computation in the form of information processing. Under the Church-Turing thesis, these models have been successful to describe any possible effective procedure construed as an algorithmic process.

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      How does abstraction change from low- to high-level programming languages?Moving up the ladder of abstraction from low- to high-level computations resembles the paradigm shift from low- to high-level programming languages. It is also analogous to the change in per-spective from concrete mathematical structures to high-level ones (as in Category Theory).

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      How have computing models changed over the last 30 years?VI. CONCLUSIONS Computing models, languages, and architecture have not changed very much over the last thirty years. Appli- cations of new computing models, languages, and ma- chines to numerical and nonnumerical computations show promise. The market is responding to the availability of such machines for intelligence computations.

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      What is an example of a computational complexity course?For example, a course on concrete computational complexity can be assembled around Chapters 10 and 11, which examine tradeoffs between space and time in primary and secondary memory. This course would presume or include introductory material from Chapter 3.

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