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This is the first book that renders a thorough discussion of systems science. It draws on material from an extensive collection of external sources, including several other books and a special library collection complete with videotape empirical evidence of applicability of the theory to a wide variety of circumstances. This is essential because systems science must be responsive to diverse human situations of the widest difficulty, and it must fill the void that the specific sciences cannot fill, because these sciences are insensitive to the necessities of reconciling disparate views of multiple observers, and incorporating local conditions in hypotheses that precede inductive explorations. Sample Chapter(s). Chapter 1: Unlimited Scope of System Science (195 KB). Contents: Foundations: The Chapters; Discovery: The Chapters; Resolution: The Chapters; The Practitioners (OC SystemistsOCO): The Chapters; Systems Science: The Chapters; Appendices: Gallery; The OC Warfield Special CollectionOCO at the George Mason University Fenwick Library; Discovering Systems Science; Linguistic Adjustments: Precursors to Understanding Complexity; The Two Neutral Processes of Systems Science; Statements, Themes, Findings, Structure; Literacy in Structural Graphics: The Higher Education Imperative. Readership: Graduate students, academics and practitioners in business management, computer science and engineering."
Computer solutions to many difficult problems in science and engineering require the use of automatic search methods that consider a large number of possible solutions to the given problems. This book describes recent advances in the theory and practice of one such search method, called Genetic Algorithms. Genetic algorithms are evolutionary search techniques based on principles derived from natural population genetics, and are currently being applied to a variety of difficult problems in science, engineering, and artificial intelligence.
Design and Analysis of Integrated Manufacturing Systems is a fresh look at manufacturing from a systems point of view. This collection of papers from a symposium sponsored by the National Academy of Engineering explores the need for new technologies, the more effective use of new tools of analysis, and the improved integration of all elements of manufacturing operations, including machines, information, and humans. It is one of the few volumes to include detailed proposals for research that match the needs of industry.
Most artificial intelligence research investigates intelligent behavior for a single agent--solving problems heuristically, understanding natural language, and so on. Distributed Artificial Intelligence (DAI) is concerned with coordinated intelligent behavior: intelligent agents coordinating their knowledge, skills, and plans to act or solve problems, working toward a single goal, or toward separate, individual goals that interact. DAI provides intellectual insights about organization, interaction, and problem solving among intelligent agents. This comprehensive collection of articles shows the breadth and depth of DAI research. The selected information is relevant to emerging DAI technologies as well as to practical problems in artificial intelligence, distributed computing systems, and human-computer interaction. "Readings in Distributed Artificial Intelligence" proposes a framework for understanding the problems and possibilities of DAI. It divides the study into three realms: the natural systems approach (emulating strategies and representations people use to coordinate their activities), the engineering/science perspective (building automated, coordinated problem solvers for specific applications), and a third, hybrid approach that is useful in analyzing and developing mixed collections of machines and human agents working together. The editors introduce the volume with an important survey of the motivations, research, and results of work in DAI. This historical and conceptual overview combines with chapter introductions to guide the reader through this fascinating field. A unique and extensive bibliography is also provided.
Fundamental Process Control focuses on the fundamental nature of process control, which includes an extensive discussion on control methodologies. The first seven chapters are devoted to the development of a complete control problem formulation that contains all the elements of practical importance. Due to the novelty of these ideas, no rigorous mathematical proofs yet exist for the assertions made, although they have been verified through simulation and experience in practice. The concepts discussed in Chapters 8 and 9 contain ideas for future developments in process control that will trigger the imagination of researchers in the fields covered. This book requires a thorough grounding in both classical and modern control theory in order to grasp the material presented. This book is therefore not for casual readers, but rather is directed at those who are currently, or those who desire to develop into, control design experts. Within the academic community, this book is ideal for the graduate level and for those academics pursuing fundamental research topics in process control.