The core belief underlying this book is that the most useful and effective models to strengthen our intelligence are system ones, developed following the logic of Systems Thinking. Such models can explore complexity, dynamics, and change, and it is the author's view that intelligence depends on the ability to construct models of this nature. The book is designed to allow the reader not only to acquire simple information on Systems Thinking but above all to gradually learn the logic and techniques that make this way of thinking an instrument for the improvement of intelligence. In order to aid the learning and practice of the Systems Thinking discipline, the author has abandoned a rigid formal language for a more discursive style. He writes in the first person, with an ample number of citations and critical analyses, and without ever giving in to the temptation to use formal mathematics.

This book presents a new understanding on how control systems truly operate, and explains how to recognize, simulate, and improve control systems in all fields of activity. It also reveals the pervasive, ubiquitous and indispensable role of control processes in our life and the need to develop a "control-oriented thinking"-based on uncomplicated but effective models derived from systems thinking-that is, a true "discipline of control." Over the book's thirteen chapters, Piero Mella shows that there are simple control systems (rather than complex ones) that can easily help us to manage complexity without drawing upon more sophisticated control systems. It begins by reviewing the basic language of systems thinking and the models it allows users to create. It then introduces the control process, presenting the theoretical structure of three simple control systems we all can observe in order to gain fundamental knowledge from them about the basic structure of a control system. Then, it presents the anatomy of the simplest "magic ring" and the general theoretical model of any control system. This is followed by an introduction to a general typology of control systems and a broader view of control systems by investigating multi-lever control systems and multi-objective systems. The book undertakes the concepts through various environments, increasingly broader in scope to suggest to readers how to recognize therein control systems manifestations in everyday life and in natural phenomena. Updated for the 2nd edition, new chapters explore control systems regulating the biological environment and the organizations, with an in-depth study of the control of quality, productivity, production, stocks and costs. Finally, it concludes by dealing with the learning process, problem-solving, and designing the logical structure of control systems.

This study adopts the logic of Systems Thinking and Control Systems, presenting a simple but complete theory called the Theory of Combinatory Systems. This new theory is able to describe, interpret, explain, simulate and control collective phenomena and their observable effects. Despite specific differences among these phenomena - many of which are "one way", non-repeatable or reproducible - they can all be described or explained, and thus understood, using the model, as simple as it is general, of combinatory systems; that is, systems formed by collectivities, or populations of non-connected and unorganized individuals of some species, which appear to be directed by an invisible hand that guides the analogous actions of similar individuals in order to produce an emerging collective phenomenon. Combinatory Systems function due to the presence of micro control systems which, operating at the individual level, lead to uniform micro behavior by individuals in order to eliminate the (gap) with respect to the objective that is represented - or revealed - by the global information (macro behavior or effect). The book also examines Combinatory Automata, which represent a powerful tool for simulating the most relevant combinatory systems. In stochastic combinatory automata, when both probabilities and periods of transition of state are agent/time/state sensitive, the probabilistic micro behaviors are conditioned by the macro behavior of the entire system, which makes the micro-macro feedback more evident. The Combinatory Systems Theory: Understanding, Modeling and Simulating Collective Phenomena is composed of four main chapters. Chapter 1 presents the basic ideas behind the theory, which are analysed in some detail. Chapter 2 describes the heuristic models of several relevant combinatory systems observable in different environments. Chapter 3, while not making particular use of sophisticated mathematical and statistical tools, presents the Theory of Combinatory Automata and builds models for simulating the operative logic of combinatory systems. Chapter 4 tries to answer three questions: are combinatory systems "systems" in the true sense of the term? Why is this theory able to explain so many and so varied a number of phenomena, even though it is based on a very simple modus operandi? Are combinatory systems different than complex systems? The book has been written with no prerequisite required to read and understand it, in particular math, statistics and computer knowledge.

This study adopts the logic of Systems Thinking and Control Systems, presenting a simple but complete theory called the Theory of Combinatory Systems. This new theory is able to describe, interpret, explain, simulate and control collective phenomena and their observable effects. Despite specific differences among these phenomena - many of which are "one way", non-repeatable or reproducible - they can all be described or explained, and thus understood, using the model, as simple as it is general, of combinatory systems; that is, systems formed by collectivities, or populations of non-connected and unorganized individuals of some species, which appear to be directed by an invisible hand that guides the analogous actions of similar individuals in order to produce an emerging collective phenomenon. Combinatory Systems function due to the presence of micro control systems which, operating at the individual level, lead to uniform micro behavior by individuals in order to eliminate the (gap) with respect to the objective that is represented - or revealed - by the global information (macro behavior or effect). The book also examines Combinatory Automata, which represent a powerful tool for simulating the most relevant combinatory systems. In stochastic combinatory automata, when both probabilities and periods of transition of state are agent/time/state sensitive, the probabilistic micro behaviors are conditioned by the macro behavior of the entire system, which makes the micro-macro feedback more evident. The Combinatory Systems Theory: Understanding, Modeling and Simulating Collective Phenomena is composed of four main chapters. Chapter 1 presents the basic ideas behind the theory, which are analysed in some detail. Chapter 2 describes the heuristic models of several relevant combinatory systems observable in different environments. Chapter 3, while not making particular use of sophisticated mathematical and statistical tools, presents the Theory of Combinatory Automata and builds models for simulating the operative logic of combinatory systems. Chapter 4 tries to answer three questions: are combinatory systems "systems" in the true sense of the term? Why is this theory able to explain so many and so varied a number of phenomena, even though it is based on a very simple modus operandi? Are combinatory systems different than complex systems? The book has been written with no prerequisite required to read and understand it, in particular math, statistics and computer knowledge.

The core belief underlying this book is that the most useful and effective models to strengthen our intelligence are system ones, developed following the logic of Systems Thinking. Such models can explore complexity, dynamics, and change, and it is the author's view that intelligence depends on the ability to construct models of this nature. The book is designed to allow the reader not only to acquire simple information on Systems Thinking but above all to gradually learn the logic and techniques that make this way of thinking an instrument for the improvement of intelligence. In order to aid the learning and practice of the Systems Thinking discipline, the author has abandoned a rigid formal language for a more discursive style. He writes in the first person, with an ample number of citations and critical analyses, and without ever giving in to the temptation to use formal mathematics.

This book presents a new understanding on how control systems truly operate, and explains how to recognize, simulate, and improve control systems in all fields of activity. It also reveals the pervasive, ubiquitous and indispensable role of control processes in our life and the need to develop a "control-oriented thinking"-based on uncomplicated but effective models derived from systems thinking-that is, a true "discipline of control." Over the book's thirteen chapters, Piero Mella shows that there are simple control systems (rather than complex ones) that can easily help us to manage complexity without drawing upon more sophisticated control systems. It begins by reviewing the basic language of systems thinking and the models it allows users to create. It then introduces the control process, presenting the theoretical structure of three simple control systems we all can observe in order to gain fundamental knowledge from them about the basic structure of a control system. Then, it presents the anatomy of the simplest "magic ring" and the general theoretical model of any control system. This is followed by an introduction to a general typology of control systems and a broader view of control systems by investigating multi-lever control systems and multi-objective systems. The book undertakes the concepts through various environments, increasingly broader in scope to suggest to readers how to recognize therein control systems manifestations in everyday life and in natural phenomena. Updated for the 2nd edition, new chapters explore control systems regulating the biological environment and the organizations, with an in-depth study of the control of quality, productivity, production, stocks and costs. Finally, it concludes by dealing with the learning process, problem-solving, and designing the logical structure of control systems.

This brief presents an overview of Gregory Bateson's Constructivist method of Cognition. Bateson proposes a theory of cognition that is based on the abstract notion of difference that the mind distinguishes and perceives and represents information that constitutes and separates how different states are ordered, grouped, and classified. Bateson, however, does not clearly indicate how a cognitive system can develop a knowledge of reality from the perception of these differences. This book seeks to offer a scientific approach to Constructivism. Using Bateson's hypothesis, chapters discuss how our mind distinguishes and elaborates differences, allowing us to form perceptions of objects, and how these objects can be described and compared. Chapters also discuss how from differences, it is possible to construct concepts or ideas of how these can be defined and how to derive from these differences the meanings of the signs used for the structuring of languages. The brief offers a coherent structure of propositions that form an interpretative theory of the modus operandi of the human mind, which will be useful not only in shedding light on our cognitive processes, but also in laying the formal groundwork for artificial intelligence. Constructing Reality is a must-have resource for researchers and students of the cognitive sciences, as well as education sciences, and researchers and scholars of artificial intelligence, learning theory, and intelligent automata programming.