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100   $a20090421d2010      uy         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aDiagrammatic reasoning in AI /$fRobbie T. Nakatsu
205   $a1st ed.
210   $aHoboken, NJ $cWiley$dc2010
215   $a1 online resource (346 p.)
300   $aDescription based upon print version of record.
311   $a0-470-33187-9 
327   $aDIAGRAMMATIC 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
330   $aPioneering 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 inte
606   $aArtificial intelligence$xGraphic methods
606   $aArtificial intelligence$xMathematics
606   $aReasoning$xGraphic methods
615  0$aArtificial intelligence$xGraphic methods.
615  0$aArtificial intelligence$xMathematics.
615  0$aReasoning$xGraphic methods.
676   $a006.3
700   $aNakatsu$b Robbie$f1964-$01640239
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910820653403321
996   $aDiagrammatic reasoning in AI$93983690
997   $aUNINA