SOLUTION MANUAL
ARTIFICIAL INTELLIGENCE: A MODERN APPROACH
,Table of Contents
1 Introduction ...
2 Intelligent Agents ...
II Problem-Solving
3 Solving Problems By Searching ...
4 Search In Complex Environments ...
5 Adversarial Search And Games ...
6 Constraint Satisfaction Problems ...
III Knowledge, Reasoning, &
Planning
7 Logical Agents ...
8 First-Order Logic ...
9 Inference In First-Order Logic ...
10 Knowledge Representation ...
11 Automated Planning ...
IV Uncertain Knowledge And Reasoning
12 Quantifying Uncertainty ...
13 Probabilistic Reasoning ...
14 Probabilistic Reasoning Over Time ...
15 Probabilistic Programming ...
16 Making Simple Decisions ...
17 Making Complex Decisions ...
18 Multiagent Decision Making ...
V Machine Learning
19 Learning From Examples ...
, 20 Learning Probabilistic Models ...
21 Deep Learning ...
22 Reinforcement Learning ...
VI Communicating, Perceiving, And Acting
23 Natural Language Processing ...
24 Deep Learning For Natural Language Processing ...
25 Computer Vision ...
26 Robotics ...
VII
Conclusions
27 Philosophy, Ethics, And Safety Of AI ...
28 The Future Of AI
, EXERCISES A
1
INTRODUCTION
Note That For Many Of The Questions In This Chapter, We Give References Where
Answers Can Be Found Rather Than Writing Them Out—The Full Answers Would Be
Far Too Long.
1.1 What Is AI?
ExerciseA1.1.#DEFA
DefineAinAyourAownAwords:A (a)Aintelligence,A(b)AartificialAintelligence,A(c)Aagent,A(d)Ara-
Ationality,A(e)AlogicalAreasoning.
a. Dictionary Definitions Of Intelligence Talk About ―The Capacity To Acquire And
Apply Knowledge‖ Or ―The Faculty Of Thought And Reason‖ Or ―The Ability To
Comprehend A Nd Profit From Experience.‖ These Are All Reasonable Answers,
But If We Want Somet Hing Quantifiable We Would Use Something Like ―The
Ability To Act Successfully Across A Wide Range Of Objectives In Complex
Environments.‖
b. We Define Artificial Intelligence As The Study And Construction Of Agent
Programs T Hat Perform Well In A Given Class Of Environments, For A Given
Agent Architecture; Th Ey Do The Right Thing. An Important Part Of That Is
Dealing With The Uncertainty Of W Hat The Current State Is, What The Outcome
Of Possible Actions Might Be, And What Is It That We Really Desire.
c. We Define An Agent As An Entity That Takes Action In Response To Percepts From
An En Vi- Ronment.
d. We Define Rationality As The Property Of A System Which Does The ―Right
Thing‖ Giv En What It Knows. See Section 2.2 For A More Complete Discussion.
The Basic Conc Ept Is Perfect Rationality; Section ?? Describes The Impossibility
Of Achieving Perfect Rational- Ity And Proposes An Alternative Definition.
e. We Define Logical Reasoning As The A Process Of Deriving New Sentences From
Old, Su Ch That The New Sentences Are Necessarily True If The Old Ones Are
True. (Notice That Do Es Not Refer To Any Specific Syntax Or Formal Language,
But It Does Require A Well- Defined Notion Of Truth.)
ExerciseA1.1.#TURI
ReadATuring‘sAoriginalApaperAonAAIA(Turing,A1950).A InAtheApaper,AheAdiscussesAseveralAo
bjectionsAtoAhisAproposedAenterpriseAandAhisAtestAforAintelligence.AWhichAobjectionsAstillAcarry
© 2023 Pearson Education, Hoboken, NJ. All rights reserve
ARTIFICIAL INTELLIGENCE: A MODERN APPROACH
,Table of Contents
1 Introduction ...
2 Intelligent Agents ...
II Problem-Solving
3 Solving Problems By Searching ...
4 Search In Complex Environments ...
5 Adversarial Search And Games ...
6 Constraint Satisfaction Problems ...
III Knowledge, Reasoning, &
Planning
7 Logical Agents ...
8 First-Order Logic ...
9 Inference In First-Order Logic ...
10 Knowledge Representation ...
11 Automated Planning ...
IV Uncertain Knowledge And Reasoning
12 Quantifying Uncertainty ...
13 Probabilistic Reasoning ...
14 Probabilistic Reasoning Over Time ...
15 Probabilistic Programming ...
16 Making Simple Decisions ...
17 Making Complex Decisions ...
18 Multiagent Decision Making ...
V Machine Learning
19 Learning From Examples ...
, 20 Learning Probabilistic Models ...
21 Deep Learning ...
22 Reinforcement Learning ...
VI Communicating, Perceiving, And Acting
23 Natural Language Processing ...
24 Deep Learning For Natural Language Processing ...
25 Computer Vision ...
26 Robotics ...
VII
Conclusions
27 Philosophy, Ethics, And Safety Of AI ...
28 The Future Of AI
, EXERCISES A
1
INTRODUCTION
Note That For Many Of The Questions In This Chapter, We Give References Where
Answers Can Be Found Rather Than Writing Them Out—The Full Answers Would Be
Far Too Long.
1.1 What Is AI?
ExerciseA1.1.#DEFA
DefineAinAyourAownAwords:A (a)Aintelligence,A(b)AartificialAintelligence,A(c)Aagent,A(d)Ara-
Ationality,A(e)AlogicalAreasoning.
a. Dictionary Definitions Of Intelligence Talk About ―The Capacity To Acquire And
Apply Knowledge‖ Or ―The Faculty Of Thought And Reason‖ Or ―The Ability To
Comprehend A Nd Profit From Experience.‖ These Are All Reasonable Answers,
But If We Want Somet Hing Quantifiable We Would Use Something Like ―The
Ability To Act Successfully Across A Wide Range Of Objectives In Complex
Environments.‖
b. We Define Artificial Intelligence As The Study And Construction Of Agent
Programs T Hat Perform Well In A Given Class Of Environments, For A Given
Agent Architecture; Th Ey Do The Right Thing. An Important Part Of That Is
Dealing With The Uncertainty Of W Hat The Current State Is, What The Outcome
Of Possible Actions Might Be, And What Is It That We Really Desire.
c. We Define An Agent As An Entity That Takes Action In Response To Percepts From
An En Vi- Ronment.
d. We Define Rationality As The Property Of A System Which Does The ―Right
Thing‖ Giv En What It Knows. See Section 2.2 For A More Complete Discussion.
The Basic Conc Ept Is Perfect Rationality; Section ?? Describes The Impossibility
Of Achieving Perfect Rational- Ity And Proposes An Alternative Definition.
e. We Define Logical Reasoning As The A Process Of Deriving New Sentences From
Old, Su Ch That The New Sentences Are Necessarily True If The Old Ones Are
True. (Notice That Do Es Not Refer To Any Specific Syntax Or Formal Language,
But It Does Require A Well- Defined Notion Of Truth.)
ExerciseA1.1.#TURI
ReadATuring‘sAoriginalApaperAonAAIA(Turing,A1950).A InAtheApaper,AheAdiscussesAseveralAo
bjectionsAtoAhisAproposedAenterpriseAandAhisAtestAforAintelligence.AWhichAobjectionsAstillAcarry
© 2023 Pearson Education, Hoboken, NJ. All rights reserve
