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Artificial Intelligence A Modern Approach
Third Editiom
BY
Stuart Russell
&
Peter Norving
Overview of the book
The main unifying theme is the idea of an intelligent agent. We define Al as the study of agents that receive percepts from the environment and perform actions. Each such agent im-plements a function that maps percept sequences to actions, and we cover different ways to represent these functions, such as reactive agents, real-time planners, and decision-theoretic systems. We explain the role of learning as extending the reach of the designer into unknown environments, and we show how that role constrains agent design, favoring explicit knowl- edge
representation and reasoning. We treat robotics and vision not as independently defined problems, but as occurring in the service of achieving, goals. We stress the importance of the NEN TERM task environment in determining the appropriate agent design.
Our primary aim is to convey the ideas that have emerged over the past fifty years of Al research and the past two millennia of related work. We have tried to avoid excessive formality in the presentation of these ideas while retaining precision. We have included pseudo code algorithms to make the key ideas concrete; our pseudocode is described in Appendix B.
This book is primarily intended for use in an undergraduate course or course sequence.The book has 27 chapters, each requiring about a week's worth of lectures, so working through the whole book requires a two-semester sequence. A one-semester course can use selected chapters to suit the interests of the instructor and students. The book can also be used in a graduate-level course (perhaps with the addition of some of the primary sources
suggested in the bibliographical notes).The only prerequisite is familiarity with basic concepts of computer science (algorithms, data structures, complexity) at a sophomore level. Freshman calculus and linear algebra are useful for some of the topics; the required mathematical back - ground is supplied in Appendix A.
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