Interactive Granular Computations in Networks and Systems Engineering: A Practical Perspective

Many scientists consider understanding intelligence as the greatest contemporary problem in science and engineering.

This book includes a concise summary and analysis of the conclusions, drawn from the completion of many complex projects, both described in literature and experienced by the author himself.

Roughly speaking, a complex system can be understood as the one whose the elements are difficult to separate. We may find examples of complex systems all around us [18, 346]: cells are composed of interacting molecules, brains are composed of interacting neurons, societies are composed of interacting individuals, ecosystems are composed of interacting species.

A deeper analysis shows that the motivation behind the research, outlined in Chap. 1 is related to conducting a search for the guidelines, which will ensure a better understanding of the answers to the following questions.

The present book consists of the following parts.

Going beyond mythology as a way to explaining the world the ancient Greek philosophers introduced science based on reason, evidence, and ontology linked to verifiable experiments.

In everyday life, one can find many mutually interactive systems that facilitate or hinder our actions. Of course, only some of them are of significance to us, whereas many others do not have any influence on our life.

Learning how to be a successful systems engineer is entirely different from learning how to excel at a traditional engineering discipline.

There are many books dedicated to CSE (e.g., see [107, 141, 192, 279, 356, 424]) which encompass essential knowledge, based on considerable experience in many domains of CSE applications.

There are many textbooks which focus on theoretical conclusions drawn from practical observations of many complex engineering projects.

CSE projects are usuallyTheory-practice gap problem (TPGP) implemented in an unpredictable and continuously changing environment.

The problems with communication and understanding user requirements are illustrated by the wit, which has been known for many decades and which is shown in Fig. 12.1.

It should be very stronglyFundamental pre-cause of CSE crisis (FP3C)FP3C – fundamental pre-cause of CSE crisis emphasized that the example of the problem in understanding the requirements (cf. Sect. 12.1) is only one of many reasons that contribute to the CSE Crisis.

At the end of the 20th century, the governments of many countries realized that there was a great need to be prepared for potential risks, resultingRiskpotential from the fact that a large part of the existing infrastructure used software which was unable to smoothly incorporate the change of dates between 1999 and 2000.

As shown by numerous reports on the implementation of complex projects and its effects, there is still no “Silver Bullet” for CSE which could effectively help achieve success.

We use the word POLTAX in the following two meanings.

AlgoTradix as an IT project, is the name of a software development project which was implemented between 2006–2011 by a group of companies organized around AdgaM Solutions under the name of AdgaM Group. The author of this book was involved to a great extent in the management of AdgaM Group.

Their aim was to develop such products, that could be used in a variety of industries and business areas.

The Excavio project was carried out by NuTech Solutions, whose background and history of formation was presented at the beginning of the discussion on the Merix project.

It was a research project carried out from 1997 to 2005, dedicated to the design of intelligent autonomous vehicles and other autonomous systems. In particular, the project focused on the development of an airborne computer system, capable of making rational decisions about the continued operation of the aircraft on the basis of various sources of knowledge, including pre-stored geographical knowledge, knowledge obtained from visual sensors and knowledge obtained through data link.

In this chapter, we present selected conclusions, drawn from the projects described in Part of the book (Case Studies), as well as many other projects.

On the basis of a substantial and practical experience in CSE, it can be said, in short, that it involves solving many complex problems, discovering some aspects of a constantly changing project and implementing mutually entangled activities among the societies of agents (including humans, computer systems and/or automatic control systems), which attempt to carry out assigned tasks through mutual interaction.

Taking into account that CSE can be treated asHuman thinking modelling problem (MT)Human thinking modelling problem (MT) the process of interactive thinking by the society of agents, one can ask the following question.

In Sect. 12.3, we have introduced potential problems associated with the misuse of non-constructive techniques of modern mathematics in CSE.

It is quite revealing that many outstanding minds reject to treat the understanding of creativity of the process of rational thinking, as the processing of grammatical statements expressed in a natural language.

One might think that great rational minds can easily handle the problem of appropriate interpretation of a language, expressing the achievements of modern science concerning the world around us. All in all, we constantly witness a rapid and spectacular progress in science and technology.

I cannot state strongly enough my conviction that the preoccupation with Consistency, so valuable for Mathematical Logic, has been incredibly destructive to those working on models of mind. At the popular level it has produced a weird conception of the potential capabilities of machines in general.

This assumption, among others, is understood in such a way that all interactions that are analyzed by us are reduced to physical phenomena.

In Chap. 13, entitled “Fundamental Pre-Cause of CSE Crisis (FP3C),” Complex systems engineering (CSE)crisispre-cause we described the interaction strategies for adaptive learning, with a particular emphasis placed on learning of “intelligent patterns of behavior” by the colonies of bacteria.

The WisTech’s approach towards “wisdom” presented in this book refers to the motto of this chapter, which is the above-quoted message of Socrates.

In Chap. 22, we have noticed that CSE projects can be treated as interactive thinking processes, implemented by the society of agents.

One of the main objectives of WisTech is

By WisTech agents, agentsinInteractionplan short, we mean agents, who comply with the WisTech postulates (i.e., FPW-01-FPW-16). For example, WisTech agents may represent human beings participating in CSE projects, IT system components, or simply agents, as understood by the AI systems.

The basic concept of WisTech, that is the concept of judgment, is treated in this book as an extension of the concept of reasoning.

In Part III of the book, we discussed problems that stems from differences between the theory and practice of CSE. The collection of these problems were referred to, in brief, as TPGP (Chap. 11).

Practical conclusions from the implementation of numerous CSE projects (cf. Part III and Part IV of this book) indicate that there still is a very large gap between theory and practice (cf. TPGP in Chap. 11).