SOLUTIONS & INSTRUCTOR MANUAL
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Artificial Intelligence: A Modern Approach, 4th Edition
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by Peter Norvig and Stuart Russell, Chapters 1 – 28
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,Artificial Intelligencev
vvvv 1 Introduction ...
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vvvv 2 Intelligent Agents ...
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II Problem-solving
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vvvv 3 Solving Problems by Searching ...
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vvvv 4 Search in Complex Environments ...
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vvvv 5 Adversarial Search and Games ...
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vvvv 6 Constraint Satisfaction Problems ...
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III Knowledge, reasoning, and planning
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vvvv 7 Logical Agents ...
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vvvv 8 First-Order Logic ...
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vvvv 9 Inference in First-Order Logic ...
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vvvv 10 Knowledge Representation ...
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vvvv 11 Automated Planning ...
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IV Uncertain knowledge and reasoning
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vvvv 12 Quantifying Uncertainty ...
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vvvv 13 Probabilistic Reasoning ...
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vvvv 14 Probabilistic Reasoning over Time ...
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vvvv 15 Probabilistic Programming ...
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vvvv 16 Making Simple Decisions ...
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vvvv 17 Making Complex Decisions ...
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vvvv 18 Multiagent Decision Making ...
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V Machine Learning
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,vvvv 19 Learning from Examples ...
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vvvv 20 Learning Probabilistic Models ...
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vvvv 21 Deep Learning ...
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vvvv 22 Reinforcement Learning ...
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VI Communicating, perceiving, and acting
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vvvv 23 Natural Language Processing ...
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vvvv 24 Deep Learning for Natural Language Processing ...
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vvvv 25 Computer Vision ...
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vvvv 26 Robotics ...
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VII Conclusions
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vvvv 27 Philosophy, Ethics, and Safety of AI ...
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vvvv 28 The Future of AI
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, EXERCISES v v
1
INTRODUCTION
Note that for many of the questions in this chapter, we give references where answers can be found
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rather than writing them out—the full answers would be far too long.
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1.1 What Is AI?
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Exercise 1.1.#DEFA v
Define in your own words: (a) intelligence, (b) artificial intelligence, (c) agent, (d) ra-
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tionality, (e) logical reasoning.
v v v v
a. Dictionary definitions of intelligence talk about “the capacity to acquire and apply v v v v v v v v v v v
knowledge” or “the faculty of thought and reason” or “the ability to comprehend and
v v v v v v v v v v v v v v
profit from experience.” These are all reasonable answers, but if we want something
v v v v v v v v v v v v v
quantifiable we would use something like “the ability to act successfully across a wide
v v v v v v v v v v v v v v
range of objectives in complex environments.”
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b. We define artificial intelligence as the study and construction of agent programs that
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perform well in a given class of environments, for a given agent architecture; they do the
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right thing. An important part of that is dealing with the uncertainty of what the current
v v v v v v v v v v v v v v v v
state is, what the outcome of possible actions might be, and what is it that we really desire.
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c. We define an agent as an entity that takes action in response to percepts from an envi-
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ronment.
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d. We define rationality as the property of a system which does the “right thing” given what
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it knows. See Section 2.2 for a more complete discussion. The basic concept is perfect
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rationality; Section ?? describes the impossibility of achieving perfect rational- ity and
v v v v v v v v v v v v
proposes an alternative definition.
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e. We define logical reasoning as the a process of deriving new sentences from old, such that
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the new sentences are necessarily true if the old ones are true. (Notice that does not refer to
v v v v v v v v v v v v v v v v v v
anyspecific syntaxorformallanguage, butitdoesrequire awell-definednotion of truth.)
v v v v v v v v v v v v v v v
Exercise 1.1.#TURI v
Read Turing’s original paper on AI (Turing, 1950). In the paper, he discusses several
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objections to his proposed enterprise and his testfor intelligence. Which objections stillcarry
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© 2023 Pearson Education, Hoboken, NJ. All rights reserved.
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v v v
Artificial Intelligence: A Modern Approach, 4th Edition
v v v v v v
by Peter Norvig and Stuart Russell, Chapters 1 – 28
v v v v v v v v v v
,Artificial Intelligencev
vvvv 1 Introduction ...
v v v
vvvv 2 Intelligent Agents ...
v v v v
II Problem-solving
v
vvvv 3 Solving Problems by Searching ...
v v v v v v
vvvv 4 Search in Complex Environments ...
v v v v v v
vvvv 5 Adversarial Search and Games ...
v v v v v v
vvvv 6 Constraint Satisfaction Problems ...
v v v v v
III Knowledge, reasoning, and planning
v v v v
vvvv 7 Logical Agents ...
v v v v
vvvv 8 First-Order Logic ...
v v v v
vvvv 9 Inference in First-Order Logic ...
v v v v v
vvvv 10 Knowledge Representation ...
v v v v
vvvv 11 Automated Planning ...
v v v v
IV Uncertain knowledge and reasoning
v v v v
vvvv 12 Quantifying Uncertainty ...
v v v v
vvvv 13 Probabilistic Reasoning ...
v v v v
vvvv 14 Probabilistic Reasoning over Time ...
v v v v v v
vvvv 15 Probabilistic Programming ...
v v v v
vvvv 16 Making Simple Decisions ...
v v v v v
vvvv 17 Making Complex Decisions ...
v v v v v
vvvv 18 Multiagent Decision Making ...
v v v v v
V Machine Learning
v v
,vvvv 19 Learning from Examples ...
v v v v v
vvvv 20 Learning Probabilistic Models ...
v v v v v
vvvv 21 Deep Learning ...
v v v v
vvvv 22 Reinforcement Learning ...
v v v v
VI Communicating, perceiving, and acting
v v v v
vvvv 23 Natural Language Processing ...
v v v v v
vvvv 24 Deep Learning for Natural Language Processing ...
v v v v v v v v
vvvv 25 Computer Vision ...
v v v v
vvvv 26 Robotics ...
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VII Conclusions
v
vvvv 27 Philosophy, Ethics, and Safety of AI ...
v v v v v v v v
vvvv 28 The Future of AI
v v v v
, EXERCISES v v
1
INTRODUCTION
Note that for many of the questions in this chapter, we give references where answers can be found
v v v v v v v v v v v v v v v v v
rather than writing them out—the full answers would be far too long.
v v v v v v v v v v v v
1.1 What Is AI?
v v v
Exercise 1.1.#DEFA v
Define in your own words: (a) intelligence, (b) artificial intelligence, (c) agent, (d) ra-
v v v v v v v v v v v v v
tionality, (e) logical reasoning.
v v v v
a. Dictionary definitions of intelligence talk about “the capacity to acquire and apply v v v v v v v v v v v
knowledge” or “the faculty of thought and reason” or “the ability to comprehend and
v v v v v v v v v v v v v v
profit from experience.” These are all reasonable answers, but if we want something
v v v v v v v v v v v v v
quantifiable we would use something like “the ability to act successfully across a wide
v v v v v v v v v v v v v v
range of objectives in complex environments.”
v v v v v v
b. We define artificial intelligence as the study and construction of agent programs that
v v v v v v v v v v v v
perform well in a given class of environments, for a given agent architecture; they do the
v v v v v v v v v v v v v v v v
right thing. An important part of that is dealing with the uncertainty of what the current
v v v v v v v v v v v v v v v v
state is, what the outcome of possible actions might be, and what is it that we really desire.
v v v v v v v v v v v v v v v v v v
c. We define an agent as an entity that takes action in response to percepts from an envi-
v v v v v v v v v v v v v v v v
ronment.
v
d. We define rationality as the property of a system which does the “right thing” given what
v v v v v v v v v v v v v v v
it knows. See Section 2.2 for a more complete discussion. The basic concept is perfect
v v v v v v v v v v v v v v v
rationality; Section ?? describes the impossibility of achieving perfect rational- ity and
v v v v v v v v v v v v
proposes an alternative definition.
v v v v
e. We define logical reasoning as the a process of deriving new sentences from old, such that
v v v v v v v v v v v v v v v
the new sentences are necessarily true if the old ones are true. (Notice that does not refer to
v v v v v v v v v v v v v v v v v v
anyspecific syntaxorformallanguage, butitdoesrequire awell-definednotion of truth.)
v v v v v v v v v v v v v v v
Exercise 1.1.#TURI v
Read Turing’s original paper on AI (Turing, 1950). In the paper, he discusses several
v v v v v v v v v v v v v
objections to his proposed enterprise and his testfor intelligence. Which objections stillcarry
v v v v v v v v v v v v v v
© 2023 Pearson Education, Hoboken, NJ. All rights reserved.
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