Machine Learning: An Artificial Intelligence Approach, Volume II

Michalski, Ryszard S., Jaime G. Carbonell and Tom M. Mitchell:

ISBN 10: 0934613001 / ISBN 13: 9780934613002

Published by Morgan Kaufmann 12.1986., 1986

About this Item

738 Seiten Texteintrag vorne im Buch vorhanden!! Gutes Exemplar, geringe Gebrauchsspuren, Cover/SU berieben/bestoßen, Schnitt/Papier nachgedunkelt, innen alles in Ordnung; Good copy, light signs of previous use, cover/dust jacket shows some rubbing/wear, edges/text pages show yellowing/darkening, interior in good condition B230814ah52 ISBN: 9780934613002 Sprache: Englisch Gewicht in Gramm: 1161.

Seller Inventory # 664118

Bibliographic Details

• Title: Machine Learning: An Artificial Intelligence Approach, Volume II
• Publisher: Morgan Kaufmann 12.1986.
• Publication Date: 1986
• Language: English
• ISBN 10: 0934613001
• ISBN 13: 9780934613002
• Binding: Hardcover
• Condition: Befriedigend
• Seller catalogs:
  • Romane/Erzählungen: Erzählungen, Romane, Essays

About this title

Synopsis

Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs―particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV and V discuss learning from observation and discovery, and learning from instruction, respectively. Part VI presents two studies on applied learning systems―one on the recovery of valuable information via inductive inference; the other on inducing models of simple algebraic skills from observed student performance in the context of the Leeds Modeling System (LMS).
This book is intended for researchers in artificial intelligence, computer science, and cognitive psychology; students in artificial intelligence and related disciplines; and a diverse range of readers, including computer scientists, robotics experts, knowledge engineers, educators, philosophers, data analysts, psychologists, and electronic engineers.

About the Author

By Ryszard S. Michalski, Jaime G. Carbonell and Tom M. Mitchell