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Book ChapterDOI

Techniques and Knowledge Used for Adaptation During Case-Based Problem Solving

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TLDR
A process model of CBR and the used knowledge according to the different knowledge containers is introduced and the current models of adaptation are described and illustrated in an example domain.
Abstract
This paper presents a survey of different adaptation techniques and the used knowledge during adaptation. A process model of CBR and the used knowledge according to the different knowledge containers is introduced. The current models of adaptation are described and illustrated in an example domain.

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Citations
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Journal ArticleDOI

An extended cellular automaton using case‐based reasoning for simulating urban development in a large complex region

TL;DR: An extended cellular automaton in which transition rules are represented by using case‐based reasoning (CBR) techniques, which can produce more plausible results than rule‐based CA in simulating this large complex region in 1988–2002.
Journal ArticleDOI

Case-based reasoning support for online catalog sales

TL;DR: The paper considers how CBR techniques can be applied to e-commerce applications to enable intelligent sales support and reviews the limitations of ordinary databases to this task and examinesCBR techniques that can improve the usefulness of electronic catalogs.
Journal ArticleDOI

MOOC-Rec: A Case Based Recommender System for MOOCs☆

TL;DR: A system that recommends appropriate MOOCs in response to a specific request of the learner is proposed, using the Case Based Reasoning (CBR) approach and a special retrieval information technique.
Journal ArticleDOI

Knowledge engineering issues in developing a case-based reasoning application

TL;DR: It is argued that in some domains this problem analysis process can be significant and proposed an iterative methodology for addressing it and described the application of case-based reasoning to the problem of aircraft conflict resolution in a system called ISAC.
Proceedings Article

Towards a New Formal Model of Transformational Adaptation in Case-Based Reasoning

TL;DR: This paper presents a step into the direction of developing such a formal model of transformational adaptation, based on the notion of the quality of a solution to a problem, which provides a semantics for adaptation knowledge and allows us to define terms like soundness, correctness and completeness.
References
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Book

Case-based reasoning

TL;DR: Case-based reasoning as discussed by the authors is one of the fastest growing areas in the field of knowledge-based systems and the first comprehensive text on the subject is presented by a leader in this field.
Book

Case-Based Reasoning: Experiences, Lessons and Future Directions

TL;DR: This book presents a selection of recent progress, issues, and directions for the future of case-based reasoning, and experimentally examines one of the fundamental tenets of CBR, that reasoning from prior experiences improves performance.
Book

Derivational analogy: a theory of reconstructive problem solving and expertise acquisition

TL;DR: Derivational analogy, a method of solving problems based on the transfer of past experience to new problem situations, is discussed in the context of other general approaches to problem solving.
Book

Planning and Learning by Analogical Reasoning

TL;DR: The problem solver automates the generation of problem solving cases and automates case storage, leading to efficient case retrieval and analogical replay.

The Knowledge Contained in Similarity Measures

TL;DR: Of which nature is the knowledge a similarity measure can contain?