Artificial Intelligence: A Modern Approach, 4th Edition
by Peter Norvig and Stuart Russell, Chapters 1 – 28
,Artificial Intelligence nw
nwnwnwnw 1 Introduction ...
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nwnwnwnw 2 Intelligent Agents ...
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II Problem-solving
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nwnwnwnw 3 Solving Problems by Searching ...
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nwnwnwnw 4 Search in Complex Environments ...
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nwnwnwnw 5 Adversarial Search and Games ...
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nwnwnwnw 6 Constraint Satisfaction Problems ...
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III Knowledge, reasoning, and planning
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nwnwnwnw 7 Logical Agents ...
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nwnwnwnw 8 First-Order Logic ...
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nwnwnwnw 9 Inference in First-Order Logic ...
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nwnwnwnw 10 Knowledge Representation ...
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nwnwnwnw 11 Automated Planning ...
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IV Uncertain knowledge and reasoning
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nwnwnwnw 12 Quantifying Uncertainty ...
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nwnwnwnw 13 Probabilistic Reasoning ...
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nwnwnwnw 14 Probabilistic Reasoning over Time ...
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nwnwnwnw 15 Probabilistic Programming ...
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nwnwnwnw 16 Making Simple Decisions ...
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nwnwnwnw 17 Making Complex Decisions ...
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nwnwnwnw 18 Multiagent Decision Making ...
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V Machine Learning
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, 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 n w n w
1
INTRODUCTION
Note that for many of the questions in this chapter, we give references where answers can
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be found 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 nw
Define in your own words: (a) intelligence, (b) artificial intelligence, (c) agent, (d) ra-
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tionality, (e) logical reasoning.
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a. Dictionary definitions of intelligence talk about “the capacity to acquire and apply
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knowledge” or “the faculty of thought and reason” or “the ability to comprehend a
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nd profit from experience.” These are all reasonable answers, but if we want some
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thing quantifiable we would use something like “the ability to act successfully across
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a wide range of objectives in complex environments.”
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b. We define artificial intelligence as the study and construction of agent programs t
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hat perform well in a given class of environments, for a given agent architecture; t
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hey do the right thing. An important part of that is dealing with the uncertainty of
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what the current state is, what the outcome of possible actions might be, and what
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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 en
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vi- ronment. nw
d. We define rationality as the property of a system which does the “right thing” giv
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en what it knows. See Section 2.2 for a more complete discussion. The basic con
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cept is perfect rationality; Section ?? describes the impossibility of achieving perfect
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rational- ity and proposes an alternative definition.nw nw nw nw nw nw
e. We define logical reasoning as the a process of deriving new sentences from old, suc
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h that the new sentences are necessarily true if the old ones are true. (Notice that does
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not refer to any specific syntax or formal language, but it does require a well-
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defined notion of truth.) nw nw nw
Exercise 1.1.#TURI nw
Read Turing’s original paper on AI (Turing, 1950). In the paper, he discusses several o
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bjections to his proposed enterprise and his test for intelligence. Which objections still carry
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© 2023 Pearson Education, Hoboken, NJ. All rights reserv
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ed.