Prologue

George Stephanopoulos; Chonghun Han

The adjective “intelligent” in the term “intelligent systems” is a misnomer. No one has ever claimed that an intelligent system in an engineering application possesses the kind of intelligence that allows it to induce new knowledge, (1) or “to contemplate its creator, or how it evolved to be the system that it is”. (2) Åström and McAvoy (3) have suggested terms such as “knowledgeable” and “informed” to accentuate the fact that these software systems depend on large amounts of (possibly) fragmented and unstructured knowledge. For the purposes of this book, the term “intelligent system” always implies a computer program, and although the quotation marks around the adjective intelligent may be dropped occasionally, no one should perceive it as a computer program with attributes of human-like intelligence. Instead, the reader should interpret the adjective as characterizing a software artifact that possesses a computational procedure, an algorithm, which attempts to “model and emulate,” and thus automate an engineering task that used to be carried out informally by a human. Whether or not this models the actual cognitive process in a human is beyond the scope of this book.

In the wide spectrum of engineering activities, collectively known as process engineering and encompassing tasks from product and process development through process design and optimization to process operations and control, so-called intelligent systems have played an important role. Ten years ago the broad introduction of knowledge-based expert systems created a pop culture that started affecting many facets of process engineering work. Expert systems were followed by their cousins, fuzzy systems, and the explosion in the use of neural networks. During the same period, the object-oriented programming (OOP) paradigm, one of the most successful “products” of artificial intelligence, has led to a revolutionary rethinking of programming practices, so that today OOP is the paradigm of choice in software engineering. After 10 years of work, 15 books/monographs/edited volumes, over 700 identified papers in archival research and professional journals, 65 reviews/tutorial/industrial survey papers, about 150 Ph.D. theses, and several thousand industrial applications worldwide, (4) the area of what is known as “intelligent systems” has turned from fringe to mainstream in a large number of process engineering activities. These include monitoring and analysis of process operations, fault diagnosis, supervisory control, feedback control, scheduling and planning of process operations, simulation, and process and product design. The early emphasis on tools and methodologies, originated by research in artificial intelligence, has given place to more integrative approaches, which focus more on the engineering problem and its characteristics. So, today, one does not encounter as frequently as 10 years ago conference sessions with titles including terms such as “expert systems,” “knowledge-based systems,” or “artificial intelligence.” Instead one sees many more mature contributions, from both the academic and industrial worlds, in mainstream engineering sessions, with significant components of what one would have earlier termed “intelligent systems.” The evolving complementarity in the use of approaches from artificial intelligence, systems and control theory, mathematical programming, and statistics is a strong indication of the maturity that the area of intelligent systems is reaching.

A THE CURRENT SETTING

The explosive growth of academic research and industrial practice in the synthesis, analysis, development, and deployment of intelligent systems is a natural phase in the saga of the Second Industrial Revolution. If the First Industrial Revolution in 18th century England ushered the world into an era characterized by machines that extended, multiplied, and leveraged human physical capabilities, the Second, currently in progress, is based on machines that extend, multiply, and leverage human mental abilities. (5) The thinking man, Homo sapiens, has returned to its Platonic roots where “all virtue is one thing, knowledge.” Using the power and versatility of moderm computer science and technology, software systems are continuously developed to preserve knowledge for it is perishable, clone it for it is scarce, make it precise for it is often vague, centralize it for it is dispersed, and make it portable for it is difficult to distribute. The implications are staggering and have already manifested themselves, reaching the most remote corners of the earth and the inner sancta of our private lives. In this expanding pervasiveness of computers, intelligent systems can affect and are affecting the way we educate, entertain, and govern ourselves, communicate with each other, overcome physical and mental disabilities, and produce material wealth. Computer-based deployment of “knowledge” has been thrust by modern sociologists into the center of our culture as the force most effective in resolving inequities in the distribution of biological, historical and material inheritance. But what is the tangible evidence? Software systems have been composed to do the following: (5–7) (i) harmonize chorales in the style of Johann Sebastian Bach and automate musical compositions into new territories; (ii) write original stanzas and poems with thematic uniformity, which could pass as human creations for about half of the polled readers; (iii) compose original drawings and “photographs” of nonexistent worlds; (iv) “author” complete books.

Equally impressive are the results in engineering and science. Characterized as “knowledgeable,” “informed,” “expert,” “intelligent,” or any other denotation, software systems have expanded tremendously the scope of automation in scientific and engineering activities. (4–13)

B THE THEORETICAL SCOPE AND LIMITATIONS OF INTELLIGENT SYSTEMS

So what? a skeptic may ask. Are the above examples manifestations of the computer’s long-awaited, human-like intelligence? No one familiar with Gödel’s theorem of incompleteness would ask such a question, (14,15) for this theorem states that it is not possible to create a formal system that is both consistent and complete. As such, you cannot create a software system based on some sort of a formal system, i.e., a consistent set of axioms, which can reflect upon itself and discover (not invent) a new dimension of knowledge. (1)

Indeed, whenever you focus your attention on any of the so-called intelligent systems, and you take the time to learn the mechanisms they use to generate their marvelous and wondrous behavior, you come up with the anti-climactic realization that everything is quite ordinary and perfectly expectable with no surprises or mystical insights. Such reaction reminds us of how Sherlock Holmes reacted when a man questioned the brilliance of his deductive reasoning in solving one of his cases:

Similarly, Alan Turing, the father of the digital computer and creator of the Turing Test for checking the “intelligence” of a machine, put it this way:

C THE CHARACTER OF THE TEN PARADIGMS

All the paradigms of intelligent systems in this volume have plans and assume extensive amounts of knowledge. As such they are ordinary computer programs and they emulate a precise computational procedure, which uses a predefined set of data. In the Aristotelian form, “all instruction given or received (by the intelligent systems) by way of argument, proceeds from preexistent knowledge.” Consequently, one should see all cases put forward by the individual chapters as nothing more than paradigms for new uses of the computer. Every one of them carries out deduction from a predefined set of knowledge, using explicit reasoning strategies. The reader should not search for inductive generation of new knowledge, even when the terms “induction” and “inductive reasoning” have been loosely employed in some chapters. Instead, the reader should see each chapter as a computer-based paradigm in capturing, articulating, and utilizing various forms of knowledge. As a result, the reader will notice that the ten chapters of this volume serve...