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FIgUre 21-8 The Recordset Paging server behaviors identify your selected target, whether it is an image or text.

To this end, I borrow heavily from AI and hence the title of the book is Diagrammatic Reasoning in AI I could just as easily have titled the book simply Diagrammatic Reasoning or The Visualization of Expertise, but these titles do not adequately capture how much I have borrowed from the AI discipline I look, speci cally, at expert systems, model-based reasoning, and inexact reasoning (including certainty factors and Bayesian networks) three important AI areas that have attempted to create programs capable of emulating human thinking and problem solving in various ways I also cover logic reasoning ( 4), which is a topic that has also been dealt with extensively in the AI literature A third motivation for writing this book is that there are no books that I know of on the marketplace today that address diagrammatic reasoning in a coherent or uni ed way.

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I hope to ll this void by providing a more cohesive treatment of the subject While there are a number of books about information design and graphic design that deal with the topic of diagramming, they explore the topic primarily from the perspective of illustrating principles of good graphic design There are also several books that deal with speci c diagramming notations For instance, there are books on Uni ed Modeling Language (UML), a diagramming standard used to model software systems and aid in systems development Another diagramming technique that is well covered in the literature is the decision graph and other notations used for decision analysis All these books do a ne and nimble job of describing and illustrating one speci c type of diagramming technique, but they are limited because they deal with only one type of diagram or focus on one type of reasoning methodology.

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This book, on the other hand, is intended to cover a diverse range of diagrams and reasoning methodologies, thereby exposing the reader to the larger issues surrounding diagrams I hope that by presenting many different types of diagrams and many types of applications, the reader will come away with a deeper appreciation of the power of diagrams The targeted audiences of this book are practitioners and researchers in AI and human computer interaction, programmers and designers of graphical user interfaces (including designers of web applications), and business and computing professionals who might be interested in deploying intelligent systems in their organizations This book is also suitable for noncomputing professionals who are interested in learning more about the power of diagrams Indeed, unlike many AI texts on the marketplace today, I assume no prior knowledge of AI or mathematics beyond high school algebra.

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(The one exception is when I discuss Bayesian networks, a topic that requires a basic understanding of probability theory; in 8, I provide a brief introduction to probability theory for the reader who has no prior knowledge of the subject) This book may be used as a self-learner s guide to diagrammatic reasoning and intelligent user interfaces Furthermore, the diagrammatic applications developed in this book are not targeted to any one particular audience but were created to represent diversity and to demonstrate that diagramming can be a powerful technique for everyone The book consists of nine chapters, each of which is more or less selfcontained, so that the reader can easily read any one of them, in any order, without any knowledge of the prior chapters One exception is 5, which.

Reproduced from Powersim business-simulation software. For more information on Powersim visit www.powersim.com

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