An Artificial Intelligence Approach to VLSI Design
An Artificial Intelligence Approach to VLSI Design
Chunking in Soar: The Anatomy of a General Learning Mechanism
Machine Learning
Explanation-Based Generalization: A Unifying View
Machine Learning
Explanation-Based Learning: An Alternative View
Machine Learning
Expert systems for design problem-solving using design refinement with plan selection and redesign (knowledge-based, artificial intelligence)
Learning by understanding analogies (reasoning)
Learning by understanding analogies (reasoning)
Using Analogical Reasoning for Mechanism Design
IEEE Expert: Intelligent Systems and Their Applications
Mapping and retrieval during plan reuse: a validation structure based approach
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Representation, indexing, and retrieval of biological cases for biologically inspired design
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
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The authors have developed domain-independent techniques for reasoning and learning by analogy, techniques that capture and apply problem-solving experience and that are useful for search-intensive problems found in the design domain. They have incorporated these techniques, plus nonmonotonic reasoning capability, into Argo, a tool for building knowledge-based systems that improve with use. They discuss learning from experience and also analogical reasoning and learning. They describe knowledge representation and interference in Argo and Argo's control strategy for design. An application to VLSI circuit design is provided. Various features of Argo are described.