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2020 | OriginalPaper | Chapter

Basic Concepts of the Elective Course on the Hard Computing Problems

Authors : Boris Melnikov, Elena Melnikova, Svetlana Pivneva

Published in: Convergent Cognitive Information Technologies

Publisher: Springer International Publishing

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Abstract

We consider the material of the elective course for the young students, and briefly describe both so-called hard problems and some methods necessary to develop programs for their implementation on the computer. For this, we are considering several real problems of discrete optimization. For each of them we consider both “greedy” algorithms and more complex approaches. The latter are, first of all, are considered in the description of concepts, understandable to “advanced” young students and necessary for the subsequent program implementation of the branches and bounds method and some associated heuristic algorithms. According to the authors, all this “within reasonable limits” is available for “advanced” young students of 14–15 years.
Thus, we present our view on the consideration of difficult problems and possible approaches to their algorithmization – at a level “somewhat higher than the popular science”, but “somewhat less than scientific”. And for this, the paper formulates the starting concepts which allows one of such “complications” to be carried out within the next half-year.

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Footnotes
1
“Ah, gentlemen, you know why we are here. We’ve not much time, and quite a problem here” (Andrew Lloyd Webber and Tim Rice).
 
2
Although the latter statement can also be disputed, if we consider it not as a problem of implementing the algorithm of its solution found beforehand by a person (namely, this problem is usually considered in literature not connected with artificial intelligence), but as a task of finding such a solution.
 
3
Let us also note, that in the final of the student team championship in programming in the world (according to the ACM version) back in 1992, there was a task about the mentioned nonograms.
 
4
The concept of “heuristics” will be briefly discussed below. According to the authors, the easiest example of a heuristic algorithm accessible for young students can be QuickSort, [9] etc.
 
5
This is a very important concept, but we shall not strictly define it. The meaning will always be clear from the context.
 
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Wirth, N.: Algorithms + Data Structures = Programs. Prentice Hall, Upper Saddle River (1979)MATH
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Polák, L.: Minimization of NFA using the universal automaton. Int. J. Found. Comput. Sci. 16(999), 335–341 (2005)MATH
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Melnikov, B.: Multiheuristic approach to discrete optimization problems. Cybern. Syst. Anal. 42(3), 335–341 (2006)MathSciNetCrossRef
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Makarkin, S., Melnikov, B., Trenina, M.: An approach to solving a pseudogeometric version of the traveling salesman problem. Izvestia of higher educational institutions. Volga Region. Phys. Math. Sci. 2(34), 135–147 (2015). https://​elibrary.​ru/​item.​asp?​id=​24254294. (in Russian)
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Melnikov, B., Melnikova, E., Pivneva, S., Churikova, N., Dudnikov, V., Prus, M.: Multi-heuristic and game approaches in search problems of the graph theory. In: Information Technology and Nanotechnology Proceedings, ITNT-2018, pp. 2884–2894 (2018)
Metadata
Title
Basic Concepts of the Elective Course on the Hard Computing Problems
Authors
Boris Melnikov
Elena Melnikova
Svetlana Pivneva
Copyright Year
2020
Book
Convergent Cognitive Information Technologies

Print ISBN: 978-3-030-37435-8

Electronic ISBN: 978-3-030-37436-5

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-37436-5_35

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