SOLUTIONS & INSTRUCTOR MANUAL Artificial Intelligence: A Modern Approach, 4th Edition by Peter Norvig and Stuart Russell, Chapters 1 – 28

SOLUTIONS & INSTRUCTOR MANUAL
Artificial Intelligence: A Modern Approach, 4th Edition
by Peter Norvig and Stuart Russell, Chapters 1 – 28

,Artificial Intelligence H2



H2 H2 H2 H2 1 Introduction ...
H2 H2 H2



H2 H2 H2 H2 2 Intelligent Agents ...
H2 H2 H2 H2




II Problem-solving
H2



H2 H2 H2 H2 3 Solving Problems by Searching ...
H2 H2 H2 H2 H2 H2



H2 H2 H2 H2 4 Search in Complex Environments ...
H2 H2 H2 H2 H2 H2



H2 H2 H2 H2 5 Adversarial Search and Games ...
H2 H2 H2 H2 H2 H2



H2 H2 H2 H2 6 Constraint Satisfaction Problems ...
H2 H2 H2 H2 H2



III Knowledge, reasoning, and planning
H2 H2 H2 H2



H2 H2 H2 H2 7 Logical Agents ...
H2 H2 H2 H2



H2 H2 H2 H2 8 First-Order Logic ...
H2 H2 H2 H2




H2 H2 H2 H2 9 Inference in First-Order Logic ...
H2 H2 H2 H2 H2



H2 H2 H2 H2 10 Knowledge Representation ...
H2 H2 H2 H2



H2 H2 H2 H2 11 Automated Planning ...
H2 H2 H2 H2



IV Uncertain knowledge and reasoning
H2 H2 H2 H2



H2 H2 H2 H2 12 Quantifying Uncertainty ...
H2 H2 H2 H2



H2 H2 H2 H2 13 Probabilistic Reasoning ...
H2 H2 H2 H2



H2 H2 H2 H2 14 Probabilistic Reasoning over Time ...
H2 H2 H2 H2 H2 H2



H2 H2 H2 H2 15 Probabilistic Programming ...
H2 H2 H2 H2




H2 H2 H2 H2 16 Making Simple Decisions ...
H2 H2 H2 H2 H2



H2 H2 H2 H2 17 Making Complex Decisions ...
H2 H2 H2 H2 H2



H2 H2 H2 H2 18 Multiagent Decision Making ...
H2 H2 H2 H2 H2



V Machine Learning
H2 H2

,H2 H2 H2 H2 19 Learning from Examples ...
H2 H2 H2 H2 H2



H2 H2 H2 H2 20 Learning Probabilistic Models ...
H2 H2 H2 H2 H2



H2 H2 H2 H2 21 Deep Learning ...
H2 H2 H2 H2



H2 H2 H2 H2 22 Reinforcement Learning ...
H2 H2 H2 H2




VI Communicating, perceiving, and acting
H2 H2 H2 H2



H2 H2 H2 H2 23 Natural Language Processing ...
H2 H2 H2 H2 H2



H2 H2 H2 H2 24 Deep Learning for Natural Language Processing ...
H2 H2 H2 H2 H2 H2 H2 H2



H2 H2 H2 H2 25 Computer Vision ...
H2 H2 H2 H2



H2 H2 H2 H2 26 Robotics ...
H2 H2 H2



VII Conclusions
H2



H2 H2 H2 H2 27 Philosophy, Ethics, and Safety of AI ...
H2 H2 H2 H2 H2 H2 H2 H2



H2 H2 H2 H2 28 The Future of AI
H2 H2 H2 H2

, EXERCISES H 2 H2
1
INTRODUCTION
Note H2that H2for H2many H2of H2the H2questions H2in H2this H2chapter, H2we H2give H2references H2where
H2answers H2can H2be H2found H2rather H2than H2writing H2them H2out—the H2full H2answers H2would

H2be H2far H2too H2long.



1.1 H 2 What Is AI?
H2 H2




Exercise H21.1.#DEFA
Define H2in H2your H2own H2words: H 2 (a) H2intelligence, H2(b) H2artificial H2intelligence, H2(c)
H2agent, H2(d) H2ra- H2tionality, H2(e) H2logical H2reasoning.




a. Dictionary H2definitions H2of H2intelligence H2talk H2about H2“the H2capacity H2to H2acquire
H2and H2apply H2knowledge” H2or H2“the H2faculty H2of H2thought H2and H2reason” H2or H2“the

H2ability H2to H2comprehend H2and H2profit H2from H2experience.” H 2 These H2are H2all

H2reasonable H2answers, H2but H2if H2we H2want H2something H2quantifiable H2we H2would

H2use H2something H2like H2“the H2ability H2to H2act H2successfully H2across H2a H2wide H2range

H2of H2objectives H2in H2complex H2environments.”

b. We H2define H2artificial H2intelligence H2as H2the H2study H2and H2construction H2of H2agent
H2programs H2that H2perform H2well H2in H2a H2given H2class H2of H2environments, H2for H2a

H2given H2agent H2architecture; H2they H2do H2the H2right H2thing. H 2 An H2important H2part

H2of H2that H2is H2dealing H2with H2the H2uncertainty H2of H2what H2the H2current H2state H2is,

H2what H2the H2outcome H2of H2possible H2actions H2might H2be, H2and H2what H2is H2it H2that

H2we H2really H2desire.

c. We H2define H2an H2agent H2as H2an H2entity H2that H2takes H2action H2in H2response H2to
H2percepts H2from H2an H2envi- H2ronment.

d. We H2define H2rationality H2as H2the H2property H2of H2a H2system H2which H2does H2the
H2“right H2thing” H2given H2what H2it H2knows. H 2 See H2Section H22.2 H2for H2a H2more

H2complete H2discussion. H 2 The H2basic H2concept H2is H2perfect H2rationality; H2Section

H2?? H2describes H2the H2impossibility H2of H2achieving H2perfect H2rational- H2ity H2and

H2proposes H2an H2alternative H2definition.

e. We H2define H2logical H2reasoning H2as H2the H2a H2process H2of H2deriving H2new H2sentences
H2from H2old, H2such H2that H2the H2new H2sentences H2are H2necessarily H2true H2if H2the H2old

H2ones H2are H2true. H2(Notice H2that H2does H2not H2refer H2to H2any H2specific H2syntax H2or

H2formal H2language, H2but H2it H2does H2require H2a H2well-defined H2notion H2of H2truth.)




Exercise H21.1.#TURI
Read H2Turing’s
© H22023 original
H2H2 PearsonH2paper
H2 H2onH2
Education, AI H2(Turing,
Hoboken,
H2 H2NJ. H2H21950). H 2 In H2the H2paper, H2he
All
H2rights H2reserved.
H2discusses H2several H2objections H2to H2his H2proposed H2enterprise H2and H2his H2test H2for

H2intelligence. H2Which H2objections H2still H2carry