Artificial Intelligence: Structures and Strategies for Complex

Artificial Intelligence: Structures and Strategies for Complex Problem Solving
- Accessible presentation: The combination of a thorough and balanced treatment of the theoretical foundations of intelligent problem solving with the data structures and algorithms needed for implementation provides a holistic picture for students.
- AI foundations: A unique discussion of the history of AI and social and the associated philosophical issues is presented in the early chapters.
- Applied programming languages: Example programs are written in three programming languages, Prolog, Lisp, and Java
- Applications in context: The practical applications of AI are put into context using model-based reasoning and planning examples from the NASA space program. Comments on the AI endeavor from the perspectives of philosophy, psychology and neuro-physiology give students a holistic picture of AI’s application in the real world.
- Coverage of the stochastic methodology: Stochastic natural language processing, including finite state machines, dynamic programming, and the Viterbi algorithm, is integrated into introductory chapters. Expanded stochastic approaches to reasoning in uncertain situations, including Bayesian belief networks and Markov models, are discussed in Chapter 9. New for the 6th Edition, Chapter 13, Probabilistically Based Machine Learning, covers stochastic methods that support machine learning.
- Stochastic natural language processing, including finite state machines, dynamic programming, and the Viterbi algorithm, is integrated into introductory chapters.
- Expanded stochastic approaches to reasoning in uncertain situations, including Bayesian belief networks and Markov models, are discussed in Chapter 9.
- New for the 6th Edition, Chapter 13, Probabilistically Based Machine Learning, covers stochastic methods that support machine learning.
- Presentation of agent technology and the use of ontologies are added to Chapter 7, Knowledge Presentation.
- A new machine-learning chapter, based on stochastic methods, Chapter 13, Probabilistically-Based Machine Learning. This new chapter covers stochastic approaches to machine learning, including first-order Bayesian networks, variants of hidden Markov models, inference with Markov random fields and loopy belief propagation.
- Presentation of parameter fitting with expectation maximization learning and structure learning using Markov chain Monte Carlo sampling. Use of Markov decision processes in reinforcement learning.
- Natural language processing with dynamic programming (the Earley parser) and other probabilistic parsing techniques including Viterbi, are added to Chapter 15, Understanding Natural Language.
- A new supplemental programming book is available: AI Algorithms in Prolog, Lisp and Java . Available online and in print, this book demonstrates these languages as tools for building many of the algorithms presented throughout Luger's AI book.
- References and citations are updated throughout.
Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one- or two-semester undergraduate course on AI.

In this accessible, comprehensive text, George Luger captures the essence of artificial intelligenceâ€“solving the complex problems that arise wherever computer technology is applied. Ideal for an undergraduate course in AI, the Sixth Edition presents the fundamental concepts of the discipline first then goes into detail with the practical information necessary to implement the algorithms and strategies discussed. Readers learn how to use a number of different software tools and techniques to address the many challenges faced by todayâ€™s computer scientists.
Country USA
Brand Pearson
Manufacturer Pearson
Binding Hardcover
ItemPartNumber Illustrations
UnitCount 1
Format Illustrated
EANs 9780321545893
ReleaseDate 0000-00-00

Country	USA
Brand	Pearson
Manufacturer	Pearson
Binding	Hardcover
ItemPartNumber	Illustrations
UnitCount	1
Format	Illustrated
EANs	9780321545893
ReleaseDate	0000-00-00

Artificial Intelligence: Structures and Strategies for Complex Problem Solving

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