Artificial Intelligence

Artificial Intelligence 2nd Edition

Book Description:

For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.
 
 
 
 
 
 
 
 
 

Artificial Intelligence

Book Description:

Artificial Intelligence presents dynamic new portraits of the men and women in the vanguard of this innovative field. Subjects include Alan Turing, who made the connection between mathematical reasoning and computer operations; Allen Newell and Herbert Simon, who created a program that could reason like a human being; Pattie Maes, who developed computerized agents to help people with research and shopping.






Artificial Intelligence 2nd Edition

Book Description:

Artificial Intelligence is the study of how to build or program computers to enable them to do what minds can do. This volume discusses the ways in which computational ideas and computer modeling can aid our understanding of human and animal minds. Major theoretical approaches are outlined, as well as some promising recent developments.
 
 
 
 
 
 
 
 
 

Artificial Intelligence 3rd Edition

Book Description:

Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence 







Artificial Intelligence

Book Description:

This book offers students and AI programmers a new perspective on the study of artificial intelligence concepts. The essential topics and theory of AI are presented, but it also includes practical information on data input & reduction as well as data output (i.e., algorithm usage). Because traditional AI concepts such as pattern recognition, numerical optimization and data mining are now simply types of algorithms, a different approach is needed.

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