Case-Based Reasoning : A Concise Introduction

Beatriz López

ISBN 10: 3031004345 / ISBN 13: 9783031004346

Published by Springer International Publishing, 2013

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783031004346

Bibliographic Details

• Title: Case-Based Reasoning : A Concise Introduction
• Publisher: Springer International Publishing
• Publication Date: 2013
• Language: English
• ISBN 10: 3031004345
• ISBN 13: 9783031004346
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 191H x 7D millimeters 235 millimeters width by 191 millimeters height by 7 millimeters depth
• Weight: 212 grams

About this title

Synopsis

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.

About the Author

Beatriz Lopez graduated in Computer Science from the Autonomous University of Barcelona in 1986. Two years later she joined the Artificial Intelligence Research Group of the Spanish Scientific Research Council where she received her Ph.D. in Computer Science from the Technical University of Catalonia in 1993 for the work ""Case-base reasoning of strategic plans."" From that point on, her research interest has always been around case-based reasoning and planning and scheduling, now including optimization and learning in distributed environments. She was associate professor from 1992-1995 and 1998-2000 at the Rovira Virgili University and has served as a Computer Science Engineer in several private companies. In February 2011, she co-founded Newronia, a spin-off company from the University of Girona. Since 2000, she has been a senior lecturer in the Department of Electronics, Electricity, and Automation Engineering at the University of Girona. Taught courses include Artificial Intelligence and Machine Learning, in which case-based reasoning is embedded. She is member of the Catalan Association for Artificial Intelligence (member of ECCAI) and several scientific committees.