Diagrammatic Reasoning in AI
Seiten
2009
John Wiley & Sons Inc (Verlag)
978-0-470-33187-3 (ISBN)
John Wiley & Sons Inc (Verlag)
978-0-470-33187-3 (ISBN)
A diagram can be used to graphically demonstrate cause and effect in intelligent systems, in particular, expert systems. Diagrammatic Reasoning in AI explores the use of diagrams, or graphical representations, that show how something works or makes something easier to understand.
PIONEERING WORK SHOWS HOW USING DIAGRAMS FACILITATES THE DESIGN OF BETTER AI SYSTEMS
The publication of Diagrammatic Reasoning in AI marks an important milestone for anyone seeking to design graphical user interfaces to support decision-making and problem-solving tasks. The author expertly demonstrates how diagrammatic representations can simplify our interaction with increasingly complex information technologies and computer-based information systems. In particular, the book emphasizes how diagrammatic user interfaces can help us better understand and visualize artificial intelligence (AI) systems. It examines how diagrammatic reasoning enhances various AI programming strategies used to emulate human thinking and problem-solving, including:
Expert systems
Model-based reasoning
Inexact reasoning such as certainty factors and Bayesian networks
Logic reasoning
A key part of the book is its extensive development of applications and graphical illustrations, drawing on such fields as the physical sciences, macroeconomics, finance, business logistics management, and medicine. Despite such tremendous diversity of usage, in terms of applications and diagramming notations, the book classifies and organizes diagrams around six major themes: system topology; sequence and flow; hierarchy and classification; association; cause and effect; and logic reasoning. Readers will benefit from the author's discussion of how diagrams can be more than just a static picture or representation and how diagrams can be a central part of an intelligent user interface, meant to be manipulated and modified, and in some cases, utilized to infer solutions to difficult problems.
This book is ideal for many different types of readers: practitioners and researchers in AI and human-computer interaction; business and computing professionals; graphic designers and designers of graphical user interfaces; and just about anyone interested in understanding the power of diagrams. By discovering the many different types of diagrams and their applications in AI, all readers will gain a deeper appreciation of diagrammatic reasoning.
PIONEERING WORK SHOWS HOW USING DIAGRAMS FACILITATES THE DESIGN OF BETTER AI SYSTEMS
The publication of Diagrammatic Reasoning in AI marks an important milestone for anyone seeking to design graphical user interfaces to support decision-making and problem-solving tasks. The author expertly demonstrates how diagrammatic representations can simplify our interaction with increasingly complex information technologies and computer-based information systems. In particular, the book emphasizes how diagrammatic user interfaces can help us better understand and visualize artificial intelligence (AI) systems. It examines how diagrammatic reasoning enhances various AI programming strategies used to emulate human thinking and problem-solving, including:
Expert systems
Model-based reasoning
Inexact reasoning such as certainty factors and Bayesian networks
Logic reasoning
A key part of the book is its extensive development of applications and graphical illustrations, drawing on such fields as the physical sciences, macroeconomics, finance, business logistics management, and medicine. Despite such tremendous diversity of usage, in terms of applications and diagramming notations, the book classifies and organizes diagrams around six major themes: system topology; sequence and flow; hierarchy and classification; association; cause and effect; and logic reasoning. Readers will benefit from the author's discussion of how diagrams can be more than just a static picture or representation and how diagrams can be a central part of an intelligent user interface, meant to be manipulated and modified, and in some cases, utilized to infer solutions to difficult problems.
This book is ideal for many different types of readers: practitioners and researchers in AI and human-computer interaction; business and computing professionals; graphic designers and designers of graphical user interfaces; and just about anyone interested in understanding the power of diagrams. By discovering the many different types of diagrams and their applications in AI, all readers will gain a deeper appreciation of diagrammatic reasoning.
Robbie T. Nakatsu, PhD, is Associate Professor in the Department of Finance and Computer Information Systems at Loyola Marymount University. Dr. Nakatsu's research interests center on intelligent user interfaces, computer simulation modeling, and the management of information technology.
Preface vii
Chapter 1 Introduction: Working Around the Limitations of AI 1
Chapter 2 Mental Models: Diagrams in the Mind’s Eye 23
Chapter 3 Types of Diagrams 57
Chapter 4 Logic Reasoning with Diagrams 108
Chapter 5 Rule-Based Expert Systems 143
Chapter 6 Rule-Based Reasoning with Diagrams 188
Chapter 7 Model-Based Reasoning 228
Chapter 8 Inexact Reasoning with Certainty Factors and Bayesian Networks 264
Chapter 9 A Framework for Understanding Diagrammatic Reasoning 302
Index 321
| Zusatzinfo | Drawings: 0 B&W, 0 Color |
|---|---|
| Verlagsort | New York |
| Sprache | englisch |
| Maße | 161 x 244 mm |
| Gewicht | 594 g |
| Einbandart | gebunden |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Informatik ► Software Entwicklung ► User Interfaces (HCI) | |
| ISBN-10 | 0-470-33187-9 / 0470331879 |
| ISBN-13 | 978-0-470-33187-3 / 9780470331873 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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