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A Mathematical Theory of Design: Foundations, Algorithms and Applications

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Cover of 'A Mathematical Theory of Design: Foundations, Algorithms and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction and Overview
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    Chapter 2 Design as Scientific Problem-Solving
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    Chapter 3 Introductory Case Studies
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    Chapter 4 Representation of Design Artifacts
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    Chapter 5 The Idealized Design Process
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    Chapter 6 Modeling the Evolutionary Design Process
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    Chapter 7 Guided Heuristics in Engineering Design
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    Chapter 8 The Measurement of a Design Structural and Functional Complexity
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    Chapter 9 Statistical Analysis of the Time Complexity Measure
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    Chapter 10 Intelligent Advisory Tool for Design Decomposition
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    Chapter 11 Physical Design of Printed Circuit Boards: Group Technology Approach
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    Chapter 12 Physical Design of Printed Circuit Boards: Genetic Algorithm Approach
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    Chapter 13 Adaptive Learning for Successful Design
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    Chapter 14 Maintaining Consistency in the Design Process
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    Chapter 15 Constraint-Based Design of Faired Parametric Curves
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    Chapter 16 Creating a Consistent 3-D Virtual Last for Problems in the Shoe Industry
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    Chapter 17 Design of a Wormgear Reducer: A Case Study
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    Chapter 18 Adaptive Learning for Successful Flexible Manufacturing Cell Design: A Case Study
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    Chapter 19 Maintaining Design Consistency: Examples
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    Chapter 20 Cases in Evolutionary Design Processes
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    Chapter 21 Concluding Reflections
Attention for Chapter 13: Adaptive Learning for Successful Design
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Citations

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Chapter title
Adaptive Learning for Successful Design
Chapter number 13
Book title
A Mathematical Theory of Design: Foundations, Algorithms and Applications
Published by
Springer, Boston, MA, January 1998
DOI 10.1007/978-1-4757-2872-9_13
Book ISBNs
978-1-4419-4798-7, 978-1-4757-2872-9
Authors

Dan Braha, Oded Maimon, Braha, Dan, Maimon, Oded