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down its different meanings.Compare (a) with the meaning of the concept as defined in physics: power is the amount of energy transferred or converted per unit time.Write one paragraph indicating how the daily language defined in (a) may affect the practice of a scientist working with the physical concept indicated in (b).

      2 1.2 Scientific rationalities. In Example 1.3 in Section 1.4, an example of the three scientific rationalities was presented. It is your turn to follow the same steps.Find an example of scientific practices that can be related to the three rationalities.Based on (a), provide one example of each scientific rationality: (i) classical, (ii) nonclassical, and (iii) interventionist.Articulate the scientific practices defined in (a) and (b) with other practices present in the social whole.

      3 1.3 Alan Turing and theoretical computer sciences. The seminal work of Claude Shannon was presented in this chapter as the beginning of information theory. Alan Turing, a British mathematician, is also a well‐known scientist considered by many as the father of theoretical computer sciences. Let us investigate him.Read the entry “Alan Turing” from The Stanford Encyclopedia of Philosophy [16].Establish the historical background of Turing's seminal work On computable numbers, with an application to the Entscheidungsproblem [17] following Example 1.4 in Section 1.4. This is the first paragraph of the text: The ‘computable’ numbers may be described briefly as the real numbers whose expressions as a decimal are calculable by finite means. Although the subject of this paper is ostensibly the computable numbers, it is almost equally easy to define and investigate computable functions of an integral variable or a real or computable variable, computable predicates, and so forth. The fundamental problems involved are, however, the same in each case, and I have chosen the computable numbers for explicit treatment as involving the least cumbrous technique. I hope shortly to give an account of the relations of the computable numbers, functions, and so forth to one another. This will include a development of the theory of functions of a real variable expressed in terms of computable numbers. According to my definition, a number is computable if its decimal can be written down by a machine.Discuss the relation between the work presented in (b) with the more philosophically leaned (speculative) Computing Machinery and Intelligence [18]. This is the first paragraph of the text: I propose to consider the question, “Can machines think?” This should begin with definitions of the meaning of the terms “machine” and “think”. The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. If the meaning of the words “machine” and “think” are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, “Can machines think?” is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.

References

      1 1 National Institute of Standards and Technology. Cyber‐physicawl systems; 2020. Last accessed 2 October 2020. https://www.nist.gov/el/cyber-physical-systems.

      2 2 Nardelli PHJ, Kühnlenz F. Why smart appliances may result in a stupid grid: examining the layers of the sociotechnical systems. IEEE Systems, Man, and Cybernetics Magazine. 2018;4(4):21–27.

      3 3 Lewis FL. Applied Optimal Control and Estimation. Prentice Hall PTR; 1992.

      4 4 Maxwell JC. On governors. Proceedings of the Royal Society of London. 1868;16(16):270–283. 10.1098/rspl.1867.0055.

      5 5 Huurdeman AA. The Worldwide History of Telecommunications. John Wiley & Sons; 2003.

      6 6 Wiener N. Cybernetics or Control and Communication in the Animal and the Machine. MIT press; 2019.

      7 7 Gerovitch S. From Newspeak to Cyberspeak: A History of Soviet Cybernetics. MIT Press; 2004.

      8 8 Althusser L. Philosophy for Non‐Philosophers. Bloomsbury Publishing; 2017.

      9 9 Althusser L. Philosophy and the Spontaneous Philosophy of the Scientists. Verso; 2012.

      10 10 Prigogine I, Stengers I. Order Out of Chaos: Man's New Dialogue with Nature. Verso Books; 2018.

      11 11 Lepskiy V. Evolution of Cybernetics: Philosophical and Methodological Analysis. Kybernetes; 2018.

      12 12 Shannon CE. A mathematical theory of communication. The Bell System Technical Journal. 1948;27(3):379–423.

      13 13 Noble DF. Forces of Production: A Social History of Industrial Automation. Routledge; 2017.

      14 14 Feenberg A. Transforming Technology: A Critical Theory Revisited. Oxford University Press; 2002.

      15 15 Umpleby SA, Medvedeva TA, Lepskiy V. Recent developments in cybernetics, from cognition to social systems. Cybernetics and Systems. 2019;50(4):367–382.

      16 16 Hodges A., Zalta EN, editor. Alan Turing. Metaphysics Research Lab, Stanford University; 2019. Last accessed 20 October 2020. https://plato.stanford.edu/archives/win2019/entries/turing/.

      17 17 Turing AM. On computable numbers, with an application to the Entscheidungsproblem. Proceedings of the London Mathematical Society. 1937;2(1):230–265.

      18 18 Turing AM. Computing machinery and intelligence. In: Parsing the Turing Test. Robert E., Gary R., Grace B., editors. Springer, Dordrecht; 2009. pp. 23–65.

Part I

2 System

This first part of the book focuses on the main theoretical concepts that are the necessary raw material to construct the theory of cyber‐physical systems to be proposed in the second part of the book. In this chapter, we begin this journey with the concept of system. The idea is to review the different meanings of the word, starting from the dictionary definition and moving toward a more technical one, which is used in the discipline of Systems Engineering. From there, a general method to organically demarcate the boundaries of a particular functioning system and everything else (i.e. its environment) will be proposed. We will further postulate the conditions of the existence of that particular functioning system as such. These conditions are divided into three levels that articulate the relation between that particular system and its environment. Different ways to classify systems will also be presented followed by an initial analysis of Maxwell's demon – a well‐known thought experiment that was proposed to challenge the second law of thermodynamics. With this chapter, we aim to clarify the relation between the scientific domain whose object is a functioning system in general and its possible particular material realizations. In this sense, we argue that this theoretical methodology is essential not only to scientifically understand systems in general but also to engineer new or rectify particular existing systems.

2.1 Introduction

      Let me start by showing a dialogue I had with my 5‐year‐old daughter:

       What is a car?

       It is a system designed to take people from one place to another, in a faster way and with less effort than walking.

       What is a system?

       Well (…), in this case, it is a machine composed of things working together to perform some action.

       And, in the other cases?

      My goal in this brief section is to provide satisfactory answers to these two questions in italics. The first step is to check which are the definitions of “system” that the dictionary

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