Combines the theoretical foundations of intelligent problem-solving with he data structures and algorithms needed for its implementation. The book presents logic, rule, object and agent-based architectures, along with example programs written in LISP and PROLOG. The practical applications of AI have been kept within the context of its broader goal: understanding the patterns of intelligence as it operates in this world of uncertainty, complexity and change. The introductory and concluding chapters take a new look at the potentials and challenges facing artificial intelligence and cognitive science.An extended treatment of knowledge-based problem-solving is given including model-based and case-based reasoning. Includes new material on:Fundamentals of search, inference and knowledge representatioAI algorithms and data structures in LISP and PROLOProduction systems, blackboards, and meta-interpreters including planers, rule-based reasoners, and inheritance systemsMachine-learning including ID3 with bagging and boosting, explanation based learning, PAC learning, and other forms of inductioNeural networks, including perceptrons, back propogation, Kohonen networks, Hopfield networks, Grossberg learning, and counterpropagationEmergent and social methods of learning and adaptation, including genetic algorithms, genetic programming and artificial lifeObject and agent-based problem solving and other forms of advanced knowledge representation
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
[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.
Combines the theoretical foundations of intelligent problem-solving with he data structures and algorithms needed for its implementation. The book presents logic, rule, object and agent-based architectures, along with example programs written in LISP and PROLOG.
The practical applications of AI have been kept within the context of its broader goal: understanding the patterns of intelligence as it operates in this world of uncertainty, complexity and change.
The introductory and concluding chapters take a new look at the potentials and challenges facing artificial intelligence and cognitive science.An extended treatment of knowledge-based problem-solving is given including model-based and case-based reasoning.
Includes new material on:Fundamentals of search, inference and knowledge representatioAI algorithms and data structures in LISP and PROLOProduction systems, blackboards, and meta-interpreters including planers, rule-based reasoners, and inheritance systemsMachine-learning including ID3 with bagging and boosting, explanation based learning, PAC learning, and other forms of inductioNeural networks, including perceptrons, back propogation, Kohonen networks, Hopfield networks, Grossberg learning, and counterpropagationEmergent and social methods of learning and adaptation, including genetic algorithms, genetic programming and artificial lifeObject and agent-based problem solving and other forms of advanced knowledge representation
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Destinations, frais et délaisVendeur : Bahamut Media, Reading, Royaume-Uni
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Etat : Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1650grams, ISBN:0805311963. N° de réf. du vendeur 9789039
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Vendeur : WorldofBooks, Goring-By-Sea, WS, Royaume-Uni
Paperback. Etat : Very Good. Combines the theoretical foundations of intelligent problem-solving with he data structures and algorithms needed for its implementation. The book presents logic, rule, object and agent-based architectures, along with example programs written in LISP and PROLOG. The practical applications of AI have been kept within the context of its broader goal: understanding the patterns of intelligence as it operates in this world of uncertainty, complexity and change. The introductory and concluding chapters take a new look at the potentials and challenges facing artificial intelligence and cognitive science.An extended treatment of knowledge-based problem-solving is given including model-based and case-based reasoning. Includes new material on:Fundamentals of search, inference and knowledge representatioAI algorithms and data structures in LISP and PROLOProduction systems, blackboards, and meta-interpreters including planers, rule-based reasoners, and inheritance systemsMachine-learning including ID3 with bagging and boosting, explanation based learning, PAC learning, and other forms of inductioNeural networks, including perceptrons, back propogation, Kohonen networks, Hopfield networks, Grossberg learning, and counterpropagationEmergent and social methods of learning and adaptation, including genetic algorithms, genetic programming and artificial lifeObject and agent-based problem solving and other forms of advanced knowledge representation. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. N° de réf. du vendeur GOR001735434
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Hardcover. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 2.25. N° de réf. du vendeur G0805311963I4N00
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Vendeur : Glynn's Books, Norwich, Royaume-Uni
Hardcover. Etat : Very Good. Hb, laminated pictorial covers, xxix + 824pp. VG with marginal wear, clean contents. Covers fundamentals of search, inference and knowledge representation; AI algorithms and data structures in LISP and PROLOG; production systems, blackboards and meta-interpreters; machine-learning; neural networks; emergent and social models of learning and adaptation; object- and agent-based problem-solving and other forms of advanced knowledge representation; algorithms for reasoning under conditions of uncertainty; an extended treatment of knowledge-based problem solving; natural language-understanding algorithms including stochastic methods. N° de réf. du vendeur 042006
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Vendeur : Better World Books, Mishawaka, IN, Etats-Unis
Etat : Good. 3rd Edition. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages. N° de réf. du vendeur GRP17176833
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Vendeur : Better World Books: West, Reno, NV, Etats-Unis
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