Open AccessProceedings Article
Explanation-based indexing of cases
Ralph Barletta,William Mark +1 more
- pp 541-546
Reads0
Chats0
TLDR
Modified explanation-based learning techniques allow the use of the incomplete domain theory to justify the actions of a case with respect to the facts known when the case was originally executed.Abstract:
Proper indexing of cases is critically important to the functioning of a case-based reasoner. In real domains such as fault recovery, a body of domain knowledge exists that can be captured and brought to bear on the indexing problem-even though the knowledge is incomplete. Modified explanation-based learning techniques allow the use of the incomplete domain theory to justify the actions of a case with respect to the facts known when the case was originally executed. Demonstrably relevant facts are generalized to form primary indices for the case. Inconsistencies between the domain theory and the actual case can also be used to determine facts that are demonstrably irrelevant to the case. The remaining facts are treated as secondary indices, subject to refinement via similarity based inductive techniques.read more
Citations
More filters
Book
Handbook of Corrosion Engineering
TL;DR: In this article, the authors present an approach to accelerate and amplify the amount of damage caused by aqueous and high-temperature corrosion in a given environment and application.
Journal ArticleDOI
Case-based reasoning: A review
Ian Watson,Farhi Marir +1 more
TL;DR: The paper outlines the development of CBR in the US in the 1980s and describes the fundamental techniques ofCBR and contrasts its approach to that of model-based reasoning systems.
Journal ArticleDOI
Case-based reasoning: a research paradigm
TL;DR: The history of case-based reasoning is reviewed, including research conducted at the Yale AI Project and elsewhere, which addresses many of the technological shortcomings of standard rule-based expert systems.
Journal ArticleDOI
Examining the feasibility of a case-based reasoning model for software effort estimation
TL;DR: The Estor reasoning model, developed based on the verbal protocols of a human expert solving a set of estimation problems, was developed and was compared to those of the expert as well asThose of the function point and COCOMO estimations of the projects.
Journal ArticleDOI
The MEDIATOR: Analysis of an early case-based problem solver
TL;DR: There remain many lessons that can be learned about case-based reasoning by analyzing the MEDIATOR's behavior, and the reasons why it behaves the way it does are analyzed.
References
More filters
Journal ArticleDOI
Explanation-based generalization: a unifying view
TL;DR: This paper proposed a general, domain-independent mechanism, called EBG, that unifies previous approaches to explanation-based generalization, which is illustrated in the context of several example problems, and used to contrast several existing systems for explanation based generalization.
Journal ArticleDOI
Explanation-Based Learning: An Alternative View
Gerald DeJong,Raymond J. Mooney +1 more
TL;DR: Six specific problems with the previously proposed framework for the explanation-based approach to machine learning are outlined and an alternative generalization method to perform explanation- based learning of new concepts is presented.
Journal ArticleDOI
Maintaining organization in a dynamic long-term memory *
TL;DR: This study will present an algorithm for knowledge-based memory reorganization that includes processes for directed generalization and generalization refinement, and a fact retrieval system called CYRUS which uses the algorithm.
Proceedings Article
Reasoning about evidence in causal explanations
TL;DR: A system that solves a new problem by recalling a previous, similar problem and modifying its solution to fit the current problem with an average of two orders of magnitude less effort is described.