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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 Intelligence m
1 Introduction ...
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2 Intelligent Agents ...
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II Problem-solving
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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
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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 m m
1
INTRODUCTION
Note that for many of the questions in this chapter, we give references where answers can be
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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 m
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 and
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profit from experience.” These are all reasonable answers, but if we want something
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quantifiable we would use something like “the ability to act successfully across a wide
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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
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the right thing. An important part of that is dealing with the uncertainty of what the
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current state is, what the outcome of possible actions might be, and what is it that we
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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
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what it knows. See Section 2.2 for a more complete discussion. The basic concept is
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perfect rationality; Section ?? describes the impossibility of achieving perfect rational-
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ity and proposes an alternative definition.
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e. We define logical reasoning as the a process of deriving new sentences from old, such
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that the new sentences are necessarily true if the old ones are true. (Notice that does not
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refer to any specific syntax or formal language, but it does require a well-defined notion of
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truth.)
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Exercise 1.1.#TURI m
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 test for intelligence. Which objections still carry
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