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.
About the Author
George Luger is currently a Professor of Computer Science, Linguistics, and Psychology at the University of New Mexico. He received his PhD from the University of Pennsylvania and spent five years researching and teaching at the Department of Artificial Intelligence at the University of Edinburgh.
