Artificial Intelligence: Structures and Strategies for Complex Problem Solving - Couverture rigide

Luger, George F.

Couverture rigide

ISBN 10 : 0201648660 ISBN 13 : 9780201648669

Editeur : Pearson Education Limited, 2001

Synopsis

Book by Luger George F

A propos du livre

Quatrième de couverture

[Shelving Category: Artificial Intelligence]

"One of the few books on the market that covers all the topics I have included in my course for the past 10 years." Bruce Maxim, University of Michigan �?? Dearborn

"The book is a perfect complement to an AI course. It gives the reader  both an historical point of view and a practical guide to all the techniques. It is THE book I recommend as an introduction to this field." Pascal Rebreyend, Dalarna University

"Excellent additions and improvements. I will use the 5th edition in my introduction and advanced AI courses." Peter Funk, M�?�lardalen University

"The style of writing and comprehensive treatment of the subject matter makes this a valuable addition to the AI literature." Malachy Eaton, University of Limerick

Can machines think like people? This question is the driving force behind Artificial Intelligence, but it is only the starting point of this ever-evolving, exciting discipline. AI uses different strategies to solve the complex problems that arise wherever computer technology is applied, from those areas pertaining to perception and adaptation (neural networks, genetic algorithms) to the fields of intelligent agents, natural language understanding and stochastic models.

George Luger examines complex problem solving techniques while demonstrating his enthusiasm and excitement for the study of intelligence itself. He shows how to use a number of different software tools and techniques to address the many challenges faced by today�??s computer scientists.

New to this edition

·         Brand new chapter which introduces the stochastic methodology.

·         Extended material in many sections addresses the continuing importance of agent-based problem solving and embodiment in AI technology.

·         Presentation of issues in natural language understanding, including sections on stochastic methods for language comprehension; Markov models; CART trees; mutual information clustering; and statistic based parsing.

·         Further discussion of the AI endeavor from the perspectives of philosophy, psychology, and neuro-psychology.

Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one or two semester university course on AI, as well as an invaluable reference for researchers in the field or practitioners wishing to employ the power of current AI techniques in their work.

After receiving his PhD from the University of Pennsylvania,George Lugerspent five years researching and teaching at the Department of Artificial Intelligence of the University of Edinburgh. He is currently a Professor of Computer Science, Linguistics, and Psychology at the University of New Mexico.

 

Présentation de l'éditeur

Artificial intelligence (AI) began as the quest to create machines that could think for themselves and (perhaps) out-think humans: the holy grail of computing! Over the years, while still exploring the mechanisms that enable thought, AI has evolved into a more pragmatic discipline. AI uses different strategies to solve the complex practical problems that present themselves wherever computing technology is applied. And intelligence itself is now known to be too complex to be described by any single theory - instead, a constellation of theories characterize the subject from different levels of abstraction. At the lowest levels, neural networks, genetic algorithms and other forms of computation aid understanding of adaptation, perception, embodiment, and interaction with the physical world. On a more abstract level, designers of expert systems, intelligent agents, stochastic models, and natural language understanding programs reflect the role of knowledge and social processes in creating, transmitting and sustaining knowledge. Further, logicians propose deduction, abduction, induction, truth-maintenance, and other models and modes for reasoning.  In this fourth edition, George Luger touches on all these levels of structures and strategies for complex problem solving, as well as conveying excitement for the study of intelligence itself. He shows how to use many different software tools and techniques for addressing the complex problems that challenge the modern computer scientist.

Détails de l'édition

• Éditeur: Pearson Education Limited
• Date d'édition: 2001
• ISBN 10: 0201648660
• ISBN 13: 9780201648669
• Reliure: Relié
• Langue: anglais
• Numéro d'édition: 4
• Nombre de pages: 880