Artificial intelligence / A modern approach

Enhanced descriptions from Syndetics:

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. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

Table of contents provided by Syndetics

• I Artificial Intelligence
• 1 Introduction
• 2 Intelligent Agents
• II Problem-Solving
• 3 Solving Problems by Searching
• 4 Informed Search and Exploration
• 5 Constraint Satisfaction Problems
• 6 Adversarial Search
• III Knowledge And Reasoning
• 7 Logical Agents
• 8 First-Order Logic
• 9 Inference in First-Order Logic
• 10 Knowledge Representation
• IV Planning
• 11 Planning
• 12 Planning and Acting in the Read World
• V Uncertain Knowledge And Reasoning
• 13 Uncertainty
• 14 Probabilistic Reasoning Systems
• 15 Probabilistic Reasoning Over Time
• 16 Making Simple Decisions
• 17 Making Complex Decisions
• VI Learning
• 18 Learning from Observations
• 19 Knowledge in Learning
• 20 Statistical Learning Methods
• 21 Reinforcement Learning
• VII Communicating, Perceiving, And Acting
• 22 Agents that Communicate
• 23 Text Processing in the Large
• 24 Perception
• 25 Robotics
• VIII Conclusions
• 26 Philosophical Foundations
• 27 AI: Present and Future

Author notes provided by Syndetics

Stuart Russell was born in 1962 in Portsmouth, England. He received his B.A. with first-class honours in physics from Oxford University in 1982, and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is a professor of computer science, director of the Center for Intelligent Systems, and holder of the Smith-Zadeh Chair in Engineering. In 1990, he received the Presidential Young Investigator Award of the National Science Foundation, and in 1995 he was cowinner of the Computers and Thought Award. He was a 1996 Miller Professor of the University of California and was appointed to a Chancellor's Professorship in 2000. In 1998, he gave the Forsythe Memorial Lectures at Stanford University. He is a Fellow and former Executive Council member of the American Association for Artificial Intelligence. He has published over 100 papers on a wide range of topics in artificial intelligence. His other books include The Use of Knowledge in Analogy and Induction and (with Eric Wefald) Do the Right Thing: Studies in Limited Rationality.

Peter Norvig is director of Search Quality at Google, Inc. He is a Fellow and Executive Council member of the American Association for Artificial Intelligence. Previously, he was head of the Computational Sciences Division at NASA Ames Research Center, where he oversaw NASA's research and development in artificial intelligence and robotics. Before that he served as chief scientist at Junglee, where he helped develop one of the first Internet information extraction services, and as a senior scientist at Sun Microsystems Laboratories working on intelligent information retrieval. He received a B.S. in applied mathematics from Brown University and a Ph.D. in computer science from the University of California at Berkeley. He has been a professor at the University of Southern California and a research faculty member at Berkeley. He has over 50 publications in computer science including the books Paradigms of AI Programming: Case Studies in Common Lisp, Verbmobil: A Translation System for Face-to-Face Dialog, and Intelligent Help Systems for UNIX.