Artificial Intelligence: A Modern Approach, 4th Edition
by Peter Norvig and Stuart Russell, Chapters 1 – 28Q
,Artificial Intelligence
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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 Q
1
INTRODUCTION
Note that for many of the questions in this chapter, we give references where answers can be fo
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und 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 Q
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 kno
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wledge” or “the faculty of thought and reason” or “the ability to comprehend and profit
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from experience.” These are all reasonable answers, but if we want something quantifi
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able we would use something like “the ability to act successfully across a wide range of
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objectives in complex environments.” Q Q Q
b. We define artificial intelligence as the study and construction of agent programs that p
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erform 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
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state is, what the outcome of possible actions might be, and what is it that we really des
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ire.
c. We define an agent as an entity that takes action in response to percepts from an envi-
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ronment. Q
d. We define rationality as the property of a system which does the “right thing” given w
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hat it knows. See Section 2.2 for a more complete discussion. The basic concept is perf
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ect 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 t
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hat the new sentences are necessarily true if the old ones are true. (Notice that does not ref
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er to any specific syntax or formal language, but it does require a well-
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defined notion of truth.) Q Q Q
Exercise 1.1.#TURI Q
Read Turing’s original paper on AI (Turing, 1950). In the paper, he discusses several object
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ions to his proposed enterprise and his test for intelligence. Which objections still carry
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