Issues and Applications of Case-Based Reasoning to Design

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adaptation
advanced case-based design applications
Assembly Sequence
Assembly Sequence Generation
Case Adaptation
Case Based Design System
Case Combination
Case Library
Case Memory
Case Retrieval
case retrieval techniques
cases
Category=UGC
Category=UYQE
CBR
computational design methods
Configuration Design Problem
constraint
Constraint C3
Constraint Satisfaction
Constraint Satisfaction Techniques
Constraint Violations
Design Cases
design support systems
Dimensional Adaptation
Dormant Behaviors
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eq_computing
eq_isMigrated=1
eq_isMigrated=2
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eq_non-fiction
Index Transformation
Influence Graph
Knowledge Source
library
mechanical device modeling
memory
problem-solving in engineering
problems
reasoning from experience
retrieval
Retrieval Methods
Ro Om
satisfaction
Selected Design Case
Skeletal Plan
system
topological
Topological Adaptation

Product details

  • ISBN 9780805823127
  • Weight: 830g
  • Dimensions: 152 x 229mm
  • Publication Date: 01 Apr 1997
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Design is believed to be one of the most interesting and challenging problem-solving activities ever facing artificial intelligence (AI) researchers. Knowledge-based systems using rule-based and model-based reasoning techniques have been applied to build design automation and/or design decision support systems. Although such systems have met with some success, difficulties have been encountered in terms of formalizing such generalized design experiences as rules, logic, and domain models. Recently, researchers have been exploring the idea of using case-based reasoning (CBR) techniques to complement or replace other approaches to design support.

CBR can be considered as an alternative to paradigms such as rule-based and model-based reasoning. Rule-based expert systems capture knowledge in the form of if-then rules which are usually identified by a domain expert. Model-based reasoning aims at formulating knowledge in the form of principles to cover the various aspects of a problem domain. These principles, which are more general than if-then rules, comprise a model which an expert system may use to solve problems. Model-based reasoning (MBR) is sometimes called reasoning from first principles. Instead of generalizing knowledge into rules or models, CBR is an experience-based method. Thus, specific cases, corresponding to prior problem-solving experiences, comprise the main knowledge sources in a CBR system.

This volume includes a collection of chapters that describe specific projects in which case-based reasoning is the focus for the representation and reasoning in a particular design domain. The chapters provide a broad spectrum of applications and issues in applying and extending the concept of CBR to design. Each chapter provides its own introduction to CBR concepts and principles.