Case-Based Reasoning : A Concise Introduction / by Beatriz López.

Format:

Book

Author/Creator:

López, Beatriz., Author.

Series:

Synthesis Lectures on Artificial Intelligence and Machine Learning, 1939-4616

Language:

English

Subjects (All):

Artificial intelligence.

Machine learning.

Neural networks (Computer science).

Artificial Intelligence.

Machine Learning.

Mathematical Models of Cognitive Processes and Neural Networks.

Local Subjects:

Artificial Intelligence.

Machine Learning.

Mathematical Models of Cognitive Processes and Neural Networks.

Physical Description:

1 online resource (XV, 87 p.)

Edition:

1st ed. 2013.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2013.

Summary:

Case-based reasoning is a methodology with a long tradition in artificial intelligence that brings together reasoning and machine learning techniques to solve problems based on past experiences or cases. Given a problem to be solved, reasoning involves the use of methods to retrieve similar past cases in order to reuse their solution for the problem at hand. Once the problem has been solved, learning methods can be applied to improve the knowledge based on past experiences. In spite of being a broad methodology applied in industry and services, case-based reasoning has often been forgotten in both artificial intelligence and machine learning books. The aim of this book is to present a concise introduction to case-based reasoning providing the essential building blocks for the design of case-based reasoning systems, as well as to bring together the main research lines in this field to encourage students to solve current CBR challenges.

Contents:

Introduction

The Case-Base

Reasoning and Decision Making

Learning

Formal Aspects

Summary and Beyond.

ISBN:

9783031015625

3031015622