FOr Lob, Gordon, Luck, George, and Isaac -- S.J.R.
J, d
FOr Kris, Isabella, and Juliet -- P.N.
Preface
Artificial intelligence (Al) is a big field, and this is a big book. We have tried to explore the
full breadth of the field, which encompasses logic, probability, and continuous mathematics;
....,.,l'~'l'l ~ v i c e s t o
perception, reasoning, learning, and action; and everything from microelectronic devices to
robotic planetary explorers. The book is also big because we go into some depth.
The subtitle of this book is ''A Modem Approach." The intended meaning of this rather
empty phrase is that we have tried to synthesize what is now known into a common
framework, rather than trying to explain each subfield of Al in its own historical context. We
apologize to those whose subfields are, as a result, less recognizable.
New to this edition
This edition captures the changes in Al that have taken place since the last edition in 2003'
There have been important applications of Al technology, such as the widespread
deploy.
ment of practical speech recognition, machine translation, autonomous vehicles, and
household robottes. There have been algorithmic landmarks, such as the solution of the game of
checkers. And there has been a great deal of theoretical progress, particularly in areas such
as probabilistic reasoning, machine learning, and computer vision. Most important from our
point of view is the continued evolution in how we think about the field, and thus how we
.., 1 m'., c 11
organize the book. The major changes are as followst
. We place more emphasis on patially observable and nondeterministic environments,
. --,. phasis on patially observable and nondeterministic environments,
especially in the nonprobabilistic settings of search and planning. The concepts of
beliefstate (a set of possible worlds) and state estimation (maintaining the belief state)
are introduced in these settings; later in the book, we add probabilities.
. In addition to discussing the types of environments and types of agents, we now cover
.
.'',
in more depth the types of representations that an agent can use. We distinguish among
atomic representations (in which each state of the world is treated as a black box),
factored representations (in which a state is a set of attribute/value pairs), and structured
.
representations (in which the world consists of objects and relations between them).
. Our coverage of planning goes into more depth on contingent planning in partially
observable environments and includes a new approach to hierarchical planning.
. We have added new material on first-order probabilistic models, including OPen-universe
models for cases where there is uncertainty as to what objects exist.
. We have completely rewritten the introductory machine-learning chaptef, stressing a
wider variety of more modem learning algorithms and placing them on a firmer
theoretical footing.
. We have expanded coverage of Web search and information extraction, and of
tech. n 1. c 1 n 1 o fo
niques for learning from very large data sets.
. 20% of the citations in this edition are to works published after 2003'
. We estimate that about 20% of the material is brand new. The remaining 80% reflects
.
older work but has been largely rewritten to present a more unified picture of the field.
..
viI
... n n
vin Preface
Overview of the book
The main unifying theme is the idea of an intelligent agent. We define Al as the study of
ding 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
imments that receive percepts from the environment and perform actions. Each such agent
im,
piements 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
present these functions, such as reactive agents, real-time planners, and decision-theoretic
,
sVstems. We explain the role of leaminZ as extending the reach of the designer into unknown
J items. Wb 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
knowly.
edge representation and reasoning. We treat robottes and vision not as independently defined
e presentation and reasoning. We treat robottes and vision not as independently defined
',,..
problems, but as occulting in the service of achieving goals. We stress the importance of the
-..
task environment in determining the appropriate agent design.
e ppropnate 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
formal..
ltV in the Dresentation of these ideas while retaining precision. We have included pseudocode
J in the presentation of these ideas while retaining precision. We have included pseudocode
1.
algorithms to make the key ideas concrete; our pseudocode is described in Appendix B.
o J ideas concrete; our pseudocode is described in Appendix B.
mk,. k 1,... 11..
fbis 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
, 1,. 1.
selected chapters to suit the interests of the instttictor and students. The book can also be
t
,.'.
used in a graduate-level course (perhaps with the addition of some of the primary sources
.laduate-level course (perhaps with the addition of some of the primary sources
I
suggested in the bibliographical notes). Sample syllabi are available at the book's Web site,
.gested in the bibliographical notes). Sample syllabi are available at the book's Web site,
.,, - - m,,...
- i rn- k 1-o7 q,1 ac 11,...
alma. cs. berkeley. edu. The onlV Prereouisite is familiaritV with basic conceDts of
y. edu. The only prerequisite is familiarity with basic concepts of
.
commuter science (algorithms, data structures, complexity) at a sophomore level. Freshman
puter science (algorithms, data structures, complexity) at a sophomore level. Freshman
1,, 1.,,
calculus and linear algebra are useful for some of the topics, the required mathematical
backs pies, the required mathematical
back,.,.,.''.'
ground is supplied in Appendix A.
Exercises are given at the end of each chapter. Exercises requiring significant
pro..,..
gramming are marked with a keyboard icon. These exercises can best be solved by taking
advantage of the code repository at aima. cs. berkeley. edu. Some of them are large
1
enough to be considered term projects. A number of exercises require some investigation of
an to be considered term projects. A number of exercises require some investigation of
the literature, these are marked with a book icon.
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Yhroughout the book, important Doints are marked with a DOintine icon. We have
in.nout the book, important points are marked with a pointing icon. We have
in1,'.. t n,
eluded an extensive index of around 6,000 items to make it easy to find things in the book.
Wherever a new term is first defined, it is also marked in the margin.
About the Web site
.,, -,
aima. c s. berke I eV. edu, the Web site for the book, contains
y. edu, the Web site for the book, contains
.,.
. implementations of the algorithms in the book in several programming languages,
t e Programming languages,
1.
. a list of over 1000 schools that have used the book, many with links to online course
..,
matenals and svilabi.
j llabi,
.
. an annotated list of over 800 links to sites around the Web with useful Al content,
',,
. a chaptenby-chapter list of supplementary material and links,
.. -..
. instructions on how to loin a discussion group for the book,
,oin a discussion group for the book,
Preface ix
..,
. instructions on how to contact the authors with questions or comments,
1 1
.. -.
. instructions on how to report errors in the book, in the likely event that some exist, and
t, in the likely event that some exist, and
,.,,
. slides and other materials for instructors.
About the cover
ac 1.
foe cover depicts the final position from the decisive game 6 of the 1997 match between
',.
chess champion Garry Kasparov and program DEEP BLUE. Kasparov, playing Black, was
forced to resign, making this the first time a computer had beaten a world champion in a
'
chess match. Kasparov is shown at the top. TO his left is the Asimo humanoid robot and
-..
to his right is Thomas Bayes (1702--1761), whose ideas about probability as a measure of
.nt is Thomas Bayes (1702--1761), whose ideas about probability as a measure of
belief underlie much of modem Al technology. Below that we see a Mars Exploration Rovef,
,
a robot that landed on Mars in 2004 and has been exploring the planet ever since. TO the
ploring the planet ever since. TO the
.,.
nght is Alan Turing (1912--1954), whose fundamental work defined the fields of computer
ant is Alan Turing (1912--1954), whose fundamental work defined the fields of computer
.. 1,.
science in general and artificial intelligence in particular At the bottom is Shakey
(1966b b particular At the bottom is Shakey
(19661972), the first robot to combine perception, world-modeling, planning, and learning. With
choked to riroiect leader Charles Rosen (1917--2002). At the bottom right is Aristotle (384
ohakeV is protect leader Charles Rosen (1917--2002). At the bottom right is Aristotle (384
y is prOJect leader Charles Rosen (1917--2002). At the bottom right is Aristotle (384
B .C.--322 B .C.), who pioneered the study of logic; his work was state of the art until the 19th
centurV (copy of a bust by Lysippos). At the bottom left, lightly screened behind the authors'
j (copy of a bust by Lysippos). At the bottom left, lightly screened behind the authors'
.,. 1.,
names, is a planning algorithm by Aristotle from De MOtu Animalium in the original Greek.
Behind the title is a portion of the CPSC Bayesian network for medical diagnosis (Pradhan
portion of the CPSC Bayesian network for medical diagnosis (Pradhan
et al., 1994). Behind the chess board is part of a Bayesian logic model for detecting nuclear
,. n... 1
explosions from seismic signals.
Creditsi Stan HondaiGettV (Kasparaov), Library of Congress (Bayes), NASA (Mars
J, paraov), Library of Congress (Bayes), NASA (Mars
' National Museum of Rome (Aristotle), Peter Norvig (book), Ian Parker (Berkeley
rover), National Museum of Rome (Aristotle), Peter Norvig (book), Ian Parker (Berkeley
,,. \ al
skVline), Shutterstock (Asimo, Chess pieces), Time Life/Getty (Shakey, Turing).
j ), ohutterstock (Asimo, Chess pieces), Time Life/Getty (Shakey, Turing).
Acknowledgments
ac. k 1 1 1 yi h. h .hi..
Yhis book would not have been possible without the many contributors whose names did not
,.,make it to the coveL Jitendra Malik and David ForsVth wrote Chanter 24 (computer vision)
J th wrote Chapter 24 (computer vision)
, q'.
and Sebastian Thrun wrote Chapter 25 (robottes). Vibhu Mittal wrote part of Chapter 22
(natural language). Nick Hay, Mehran Sahami, and Emest Davis wrote some of the exercises.
~ ac.
Zoran Duric (George Mason), Thomas C. Henderson (Utah), Leon Reznik (RIT), Michael
GourleV (Central Oklahoma) and Emest Davis (NYU) reviewed the manuscript and made
j
helpful suggestions. We thank Emie Davis in particular for his tireless ability to read multiple
drafts and help improve the book. Nick HaV whipped the bibliography into shape and on
p improve the book. Nick Hay whipped the bibliography into shape and on
deadline staVed uD to 5:30 AM writing code to make the book betted Jon Barron formatted
J p to 5f30 AM writing code to make the book betted Jon Barron formatted
and improved the diagrams in this edition, while Tim Huang, Mark Paskin, and Cynthia
Bruvns helDed with diagrams and algorithms in previous editions. Ravi Mohan and Ciaran
j ifs helped with diagrams and algorithms in previous editions. Ravi Mohan and Ciaran
O'Reillv wrote and maintain the Java code examDles on the Web site. John CannV wrote
J pies on the Web site. John Canny wrote
the robottes chapter for the first edition and Douglas Edwards researched the historical notes.
aam n.,vil ic $l l'.,
YracV Dunkelberger, Allison Michael, Scott Disanno, and Jane Bonned at Pearson tried their
, Dunkelberger, Allison Michael, Scott Disanno, and Jane Bonned at Pearson tried their
best to keep us on schedule and made many helpful suggestions. Most helpful of all has
x Preface
been June Sussman, P.P.A., who read every chapter and provided extensive improvements. In
.,.. 1, n,, 1,
previous editions we had proofreaders who would tell us when we left out a comma and said
which when we meant that; June told us when we left out a minus sign and said fi when we
meant x4. For every typo or confusing explanation that remains in the book, rest assured that
j. for every typo or confusing explanation that remains in the book, rest assured that
June has fixed at least five. She persevered even when a power failure forced her to work by
lantern light rather than LCD glow.
at,,~rt would like to thank his Dorents for their suDI
stuart would like to thank his parents for their support and encouragement and his
.
wife, Loy Sheflott, for her endless patience and boundless wisdom. He hopes that Gordon,
LucV, George, and Isaac will soon be reading this book after they have forgiven him for
J, b 1 and Isaac will soon be reading this book after they have forgiven him for
,.,.
workinZ so long on it. RUGS (Russell's Unusual Group of Students) have been unusuallV
o ho long on it. RUGS (Russell's Unusual Group of Students) have been unusually
helpful, as always.
Peter would like to thank his parents (TOrsten and Gerda) for getting him started,
, l.. n
and his wife (Kris), children (Bella and Juliet), colleagues, and friends for encouraging and
-. -.
tolerating him through the long hours of writing and longer hours of rewriting.
b nim through the long hours of writing and longer hours of rewriting.
We both thank the librarians at Berkeley, Stanford, and NASA and the developers of
CiteSeef, Wikipedia, and Google, who have revolutionized the way we do research. We can't
,, 1,',, 1 1,.
acknowledge all the people who have used the book and made suggestions, but we would like
e people who have used the book and made suggestions, but we would like
-.,,.,
to note the especially helpful comments of Gagan Aggarwal, Eyal Amif, Ion
Androutsopoulos, Krzysztof Apt, Warren Haley Armstrong, Ellery Aziel, Jeff Van Baalen, Darius Bacon,
Brian Bakef, Shumeet Baluja, Don Barkef, TOny Barrett, James Newton Bass, Don Beal,
Howard Beck, WOlf gang Bibel, John Binder, Larry Bookman, David R. Boxall, Ronen
Brafx, n.
man, John Bresina, Gerhard Brewka, Selmer Bringsjord, Carla Brodley, Chris Brown, Emma
Brunskill, Wilhelm Burgef, Lauren Burka, Carlos Bustamante, Joao Cachopo, Murray
Campbell, Norman Carvef, Emmanuel Castro, Anti Chakiavarthy, Dan Chisarick, Berthe Choueiry,
Roberto Cipolla, David Cohen, James Coleman, June Ann Comparini, Corinna Cones, Gary
Cottrell, Emest Davis, TOm Dean, Rina Dechtef, TOm Dietterich, Peter Drake, Chuck Dyef,
Doug Edwards, Robert Egginton, Asma'a EI-Budrawy, Barbara Engelhardt, Kutluhan Erol,
Oren Etzioni, Hana Filip, Douglas Fishef, Jeffrey Forbes, Ken Ford, Eric FosleFLussief,
John Foslef, Jeremy Frank, Alex Franz, Bob Futrelle, Marek Galecki, Stefan Gerberding,
Stuart Gill, Sabine Glesnef, Seth Golub, Gosta Grahne, Russ Greinef, Eric Grimson, Bac
bara Grosz, Larry Hall, Sieve Hanks, Othar Hansson, Emst Heinz, Jim Hendlef, Christoph
Herrmann, Paul Hilfingef, Robert Holte, Vasant Honavaf, Tim Huang, Seth Hutchinson, Joost
Jacob, Mark Jelasity, Magnus Johansson, Istvan Jonyer, Dan Jurafsky, Leslie Kaelbling, Keiji
Kanazawa, Surewha Kasibhatla, Simon Kasif, Henry Kautz, Gernot Kerschbaumer, Max
Khesin, Richard Kirby, Dan Klein, Kevin Knight, Roland Koenig, Sven Koenig, Daphne
Kollef, Rich Korf, Benjamin Kuipers, James Kurien, John Lafferty, John Laird, Gus
Larsx, x X X n 1 T T
son, John Lazzaro, Jon LeBlanc, Jason Leatherman, Frank Lee, Jon Lehto, Edward Lim,
Phil Long, Pierre Louveaux, Don Loveland, Sridhar Mahadevan, TOny Mancill, Jim Martin,
Andy MaVer, John McCarthy, David McGrane, Jay Mendelsohn, Risto Miikkulanien, Brian
j. J, John McCarthy, David McGrane, Jay Mendelsohn, Risto Miikkulanien, Brian
Milch, Sieve Minion, Vibhu Mittal, Mehryar Mohri, Leora Morgenstem, Stephen Muggleton,
Kevin Mumhy, Ron Musick, Sung Myaeng, Eric Nadeau, Lee Naish, Pandu Nayak, Bernhard
phy, Ron Musick, Sung Myaeng, Eric Nadeau, Lee Naish, Pandu Nayak, Bernhard
Nebel, Stuart Nelson, XuanLong Nguyen, Nils Nilsson, Illah Nourbakhsh, Ah Noun, Arthur
Nunes-Harwitt, Sieve Omohundro, David Page, David Palmef, David Parkes, Ron Paff, Mark
Preface xi
Paskin, TOny Passera, Amit Patel, Michael Pazzani, Femando Pereira, Joseph Perla, Wim
Pi. 1 x n' 1 t x
;is, Ira Pohl, Martha Pollack, David Poole, Bruce Portef, Malcolm Pradhan, Bill Pringle, Lob
Jls, Ira Pohl, Martha Pollack, David Poole, Bruce Portef, Malcolm Pradhan, Bill Pringle, Lob
. ac.
raine Prior, Greg Provan, William Rapaport, Deepak Ravichandran, Ioannis Refanidis, Philip
Resnik, Francesca Rossi, Sam Rowels, Richard Russell, Jonathan Schaeffer, Richard Scherl,
Hinrich Schuetze, Lars Schustef, Bart Selman, Sobed Shams, Stuart Shapiro, Jude
Shavlik, YOram Singef, Satinder Singh, Daniel Sleatof, David Smith, Bryan So, Robert Sproull,
LVnn Stein, Larry Stephens, Andreas Stolcke, Paul Stradling, Devika Subramanian, Marek
j, Larry Stephens, Andreas Stolcke, Paul Stradling, Devika Subramanian, Marek
c'lchenek. Rich Sutton. Ionathan Tash, Austin Tate, Bas Terwljn, Olivier Teytaud, Michael
ouchenek, Rich Sutton, Jonathan Tash, Austin Tate, Bas Terwljn, Olivier Teytaud, Michael
ac' 'sober, William ThompQri q fustian Thrun, Eric Tiedemann, Mark TOrrance, Randall
Yhielscher, William Thompson, Sebastian Thrun, Eric Tiedemann, Mark TOrrance, Randall
Upham, Paul Utgoff, Peter van Beek, Hal Varian, Paulina Varshavskaya, Sunil Vemuri, Vandi
Verma, Ubbo Vissef, Jim Waldo, TOby Walsh, Bonnie Webbef, Dan Weld, Michael Wellman,
Kamin Whitehouse, Michael Dean White, Brian Williams, David WOlf e, Jason WOlf e, Bill
WOods, Alden Wright, Jay Yagnik, Mark Yasuda, Richard Yen, Eliezer Yudkowsky, Weixiong
=
Zhang, Ming Zhao, Shlomo Zilberstein, and our esteemed colleague Anonymous Reviewed
e, iding Zhao, Shlomo Zilberstein, and our esteemed colleague Anonymous Reviewed
About the Authors
Stuart Russell was born in 1962 in Portsmouth, England. He received his B.A. with
firstclass 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
puters 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 Rationalics
Peter Norvig is currently Director of Research at Google, Inc., and was the director
responsible for the core Web search algorithms from 2002 to 2005. He is a Fellow of the American
Association for Artificial intelligence and the Association for Computing Machinery.
PreviouslV, he was head of the Computational Sciences Division at NASA Ames Research Center,
J, ne was head of the Computational Sciences Division at NASA Ames Research Center,
where he oversaw NASA's research and development in artificial intelligence and robottes,
and chief scientist at Junglee, where he helped develop one of the first internet information
extraction services. 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 received the
Distinguished Alumni and Engineering innovation awards from Berkeley and the Exceptional
Achievement Medal from NASA. He has been a professor at the University of Southern
California and a research faculty member at Berkeley. His other books are Paradigms ofAl
Programming: Case Studies in Common LisP and Verbmobil: A Translation Systemfor
Faceto-Face Dialog and intelligent HelP Systems for UNIX.
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