SOLUTIONS & INSTRUCTOR MANUAL for Artificial
Intelligence: A Modern Approach, 4th Edition by Peter
Norvig and Stuart Russell Updated A+
,Artificial Intelligence
A
1 Introduction ...
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2 Intelligent Agents ...
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II Problem-solving
A
3 Solving Problems by Searching ...
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4 Search in Complex Environments ...
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5 Adversarial Search and Games ...
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6 Constraint Satisfaction Problems ...
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III Knowledge, reasoning, and planning
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7 Logical Agents ...
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8 First-Order Logic ...
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9 Inference in First-Order Logic ...
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10 Knowledge Representation ...
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11 Automated Planning ...
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IV Uncertain knowledge and reasoning
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12 Quantifying Uncertainty ...
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13 Probabilistic Reasoning ...
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14 Probabilistic Reasoning over Time ...
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15 Probabilistic Programming ...
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16 Making Simple Decisions ...
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17 Making Complex Decisions ...
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18 Multiagent Decision Making ...
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V Machine Learning
A A
, 19 Learning from Examples ...
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20 Learning Probabilistic Models ...
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21 Deep Learning ...
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22 Reinforcement Learning ...
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VI Communicating, perceiving, and acting
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23 Natural Language Processing ...
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24 Deep Learning for Natural Language Processing ...
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25 Computer Vision ...
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26 Robotics ...
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VII Conclusions
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27 Philosophy, Ethics, and Safety of AI ...
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28 The Future of AI
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, EXERCISES A A
1
INTRODUCTION
NoteAthatAforAmanyAofAtheAquestionsAinAthisAchapter,AweAgiveAreferencesAwhereAanswersAcan
AbeAfoundAratherAthanAwritingAthemAout—theAfullAanswersAwouldAbeAfarAtooAlong.
1.1 What Is AI?
A A A
ExerciseA1.1.#DEFA
DefineAinAyourAownAwords:A (a)Aintelligence,A(b)AartificialAintelligence,A(c)Aagent,A(d)Ara-
Ationality,A(e)AlogicalAreasoning.
a. DictionaryAdefinitionsAofAintelligenceAtalkAaboutA“theAcapacityAtoAacquireAandAapplyA
knowledge”AorA“theAfacultyAofAthoughtAandAreason”AorA“theAabilityAtoAcomprehendAa
ndAprofitAfromAexperience.”A TheseAareAallAreasonableAanswers,AbutAifAweAwantAsomet
hingAquantifiableAweAwouldAuseAsomethingAlikeA“theAabilityAtoAactAsuccessfullyAacross
AaAwideArangeAofAobjectivesAinAcomplexAenvironments.”
b. WeAdefineAartificialAintelligenceAasAtheAstudyAandAconstructionAofAagentAprogramsAt
hatAperformAwellAinAaAgivenAclassAofAenvironments,AforAaAgivenAagentAarchitecture;Ath
eyAdoAtheArightAthing.A AnAimportantApartAofAthatAisAdealingAwithAtheAuncertaintyAofAw
hatAtheAcurrentAstateAis,AwhatAtheAoutcomeAofApossibleAactionsAmightAbe,AandAwhatAisA
itAthatAweAreallyAdesire.
c. WeAdefineAanAagentAasAanAentityAthatAtakesAactionAinAresponseAtoAperceptsAfromAanAen
vi-Aronment.
d. WeAdefineArationalityAasAtheApropertyAofAaAsystemAwhichAdoesAtheA“rightAthing”Agiv
enAwhatAitAknows.A SeeASectionA2.2AforAaAmoreAcompleteAdiscussion.A TheAbasicAconc
eptAisAperfectArationality;ASectionA??AdescribesAtheAimpossibilityAofAachievingAperfectA
rational-AityAandAproposesAanAalternativeAdefinition.
e. WeAdefineAlogicalAreasoningAasAtheAaAprocessAofAderivingAnewAsentencesAfromAold,Asu
chAthatAtheAnewAsentencesAareAnecessarilyAtrueAifAtheAoldAonesAareAtrue.A(NoticeAthatAdo
esAnotAreferAtoAanyAspecificAsyntaxAorAformalAlanguage,AbutAitAdoesArequireAaAwell-
definedAnotionAofAtruth.)
ExerciseA1.1.#TURI
ReadATuring’sAoriginalApaperAonAAIA(Turing,A1950).A InAtheApaper,AheAdiscussesAseveralAo
bjectionsAtoAhisAproposedAenterpriseAandAhisAtestAforAintelligence.AWhichAobjectionsAstillAcarry
©A2023APearsonAEducation,AHoboken,ANJ.AAllArightsAreserve
d.
Intelligence: A Modern Approach, 4th Edition by Peter
Norvig and Stuart Russell Updated A+
,Artificial Intelligence
A
1 Introduction ...
AAAA A A A
2 Intelligent Agents ...
AAAA A A A A
II Problem-solving
A
3 Solving Problems by Searching ...
AAAA A A A A A A
4 Search in Complex Environments ...
AAAA A A A A A A
5 Adversarial Search and Games ...
AAAA A A A A A A
6 Constraint Satisfaction Problems ...
AAAA A A A A A
III Knowledge, reasoning, and planning
A A A A
7 Logical Agents ...
AAAA A A A A
8 First-Order Logic ...
AAAA A A A A
9 Inference in First-Order Logic ...
AAAA A A A A A
10 Knowledge Representation ...
AAAA A A A A
11 Automated Planning ...
AAAA A A A A
IV Uncertain knowledge and reasoning
A A A A
12 Quantifying Uncertainty ...
AAAA A A A A
13 Probabilistic Reasoning ...
AAAA A A A A
14 Probabilistic Reasoning over Time ...
AAAA A A A A A A
15 Probabilistic Programming ...
AAAA A A A A
16 Making Simple Decisions ...
AAAA A A A A A
17 Making Complex Decisions ...
AAAA A A A A A
18 Multiagent Decision Making ...
AAAA A A A A A
V Machine Learning
A A
, 19 Learning from Examples ...
AAAA A A A A A
20 Learning Probabilistic Models ...
AAAA A A A A A
21 Deep Learning ...
AAAA A A A A
22 Reinforcement Learning ...
AAAA A A A A
VI Communicating, perceiving, and acting
A A A A
23 Natural Language Processing ...
AAAA A A A A A
24 Deep Learning for Natural Language Processing ...
AAAA A A A A A A A A
25 Computer Vision ...
AAAA A A A A
26 Robotics ...
AAAA A A A
VII Conclusions
A
27 Philosophy, Ethics, and Safety of AI ...
AAAA A A A A A A A A
28 The Future of AI
AAAA A A A A
, EXERCISES A A
1
INTRODUCTION
NoteAthatAforAmanyAofAtheAquestionsAinAthisAchapter,AweAgiveAreferencesAwhereAanswersAcan
AbeAfoundAratherAthanAwritingAthemAout—theAfullAanswersAwouldAbeAfarAtooAlong.
1.1 What Is AI?
A A A
ExerciseA1.1.#DEFA
DefineAinAyourAownAwords:A (a)Aintelligence,A(b)AartificialAintelligence,A(c)Aagent,A(d)Ara-
Ationality,A(e)AlogicalAreasoning.
a. DictionaryAdefinitionsAofAintelligenceAtalkAaboutA“theAcapacityAtoAacquireAandAapplyA
knowledge”AorA“theAfacultyAofAthoughtAandAreason”AorA“theAabilityAtoAcomprehendAa
ndAprofitAfromAexperience.”A TheseAareAallAreasonableAanswers,AbutAifAweAwantAsomet
hingAquantifiableAweAwouldAuseAsomethingAlikeA“theAabilityAtoAactAsuccessfullyAacross
AaAwideArangeAofAobjectivesAinAcomplexAenvironments.”
b. WeAdefineAartificialAintelligenceAasAtheAstudyAandAconstructionAofAagentAprogramsAt
hatAperformAwellAinAaAgivenAclassAofAenvironments,AforAaAgivenAagentAarchitecture;Ath
eyAdoAtheArightAthing.A AnAimportantApartAofAthatAisAdealingAwithAtheAuncertaintyAofAw
hatAtheAcurrentAstateAis,AwhatAtheAoutcomeAofApossibleAactionsAmightAbe,AandAwhatAisA
itAthatAweAreallyAdesire.
c. WeAdefineAanAagentAasAanAentityAthatAtakesAactionAinAresponseAtoAperceptsAfromAanAen
vi-Aronment.
d. WeAdefineArationalityAasAtheApropertyAofAaAsystemAwhichAdoesAtheA“rightAthing”Agiv
enAwhatAitAknows.A SeeASectionA2.2AforAaAmoreAcompleteAdiscussion.A TheAbasicAconc
eptAisAperfectArationality;ASectionA??AdescribesAtheAimpossibilityAofAachievingAperfectA
rational-AityAandAproposesAanAalternativeAdefinition.
e. WeAdefineAlogicalAreasoningAasAtheAaAprocessAofAderivingAnewAsentencesAfromAold,Asu
chAthatAtheAnewAsentencesAareAnecessarilyAtrueAifAtheAoldAonesAareAtrue.A(NoticeAthatAdo
esAnotAreferAtoAanyAspecificAsyntaxAorAformalAlanguage,AbutAitAdoesArequireAaAwell-
definedAnotionAofAtruth.)
ExerciseA1.1.#TURI
ReadATuring’sAoriginalApaperAonAAIA(Turing,A1950).A InAtheApaper,AheAdiscussesAseveralAo
bjectionsAtoAhisAproposedAenterpriseAandAhisAtestAforAintelligence.AWhichAobjectionsAstillAcarry
©A2023APearsonAEducation,AHoboken,ANJ.AAllArightsAreserve
d.