Franklin

Diagrammatic Reasoning in AI : Decision-Making and Problem-Solving with Diagrams.

Author/Creator:
Nakatsu, Robbie T.
Publication:
Hoboken : John Wiley & Sons, Incorporated, 2009.
Format/Description:
Book
1 online resource (346 pages)
Edition:
1st ed.
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Subjects:
Artificial intelligence -- Graphic methods.
Artificial intelligence -- Mathematics.
Reasoning -- Graphic methods.
Form/Genre:
Electronic books.
Summary:
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.
Contents:
Intro
DIAGRAMMATIC REASONING IN AI
CONTENTS
PREFACE
ACKNOWLEDGMENTS
CHAPTER 1 INTRODUCTION: WORKING AROUND THE LIMITATIONS OF AI
CHAPTER 2 MENTAL MODELS: DIAGRAMS IN THE MIND'S EYE
CHAPTER 3 TYPES OF DIAGRAMS
CHAPTER 4 LOGIC REASONING WITH DIAGRAMS
CHAPTER 5 RULE-BASED EXPERT SYSTEMS
CHAPTER 6 RULE-BASED REASONING WITH DIAGRAMS
CHAPTER 7 MODEL-BASED REASONING
CHAPTER 8 INEXACT REASONING WITH CERTAINTY FACTORS AND BAYESIAN NETWORKS
CHAPTER 9 A FRAMEWORK FOR UNDERSTANDING DIAGRAMMATIC REASONING
INDEX.
Notes:
Description based on publisher supplied metadata and other sources.
Local notes:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2021. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Other format:
Print version: Nakatsu, Robbie T. Diagrammatic Reasoning in AI
ISBN:
9780470400722
9780470331873
OCLC:
536118806