SOLUTIONS & INSTRUCTOR MANUAL Artificial Intelligence: A Modern Approach, 4th Edition by Peter Norvig and Stuart Russell, Chapters 1 – 28

SOLUTIONS&INSTRUCTORMANUAL
N N N




ArtificialIntelligence:AModernApproach,4thEdition by
N N N N N N N




Peter Norvig and Stuart Russell, Chapters 1 – 28
N N N N N N N N N

,ArtificialIntelligence
N




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 ...
N N




III Knowledge, reasoning, and 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 vb
N N




1
INTRODUCTION
Note that for many of the questions in this chapter, we give
N N N N N N N N N N N




references where answers can be found rather
N than writing them N N N N N N




out—the full answers
N would be far too long. N N N N




1.1 What Is AI?

Exercise 1.1.#DEFA N




Define in your own words: (a) intelligence, (b) artificial intelligence, (c) agent, (d) ra- tionality,
N N N N N N N N N N N N N N




(e) logical reasoning.
N N N




a. Dictionary definitions of intelligence talk about ―the capacity N N N N N N N N N N N N N N




to acquire
N and Napply knowledge‖ or ―the Nfaculty of N N N N N N N N N N N N N N N




thoughtN and reason‖ or ―the ability to comprehend and profit from N N N N N N N N N N N




experience.‖ These are all reasonable answers, but if we want
N N N N N N N N N N N N N N N N N N N




something quantifiable we would use something like ―the ability to
N N N N N N N N N N N N N N N N N N N




act successfully across a wide range of objectives in complex
N N N N N N N N N N N N N N N N N N




environments.‖
N




b. We define artificial intelligence
N as the studyN and N N N N N N N N N N N N N




construction
N of agent programs that perform well in a given class N N N N N N N N N N N N N N N N N N N N




of environments, for
N a givenN agent architecture;
N they do the N N N N N N N N N N N N N N N




right Nthing. N An important part of that is dealing with the N N N N N N N N N N N N




uncertainty of what the current state is, what the outcome of
N N N N N N N N N N N N N N N N N N




possible actions might be, and what is it that we really desire.
N N N N N N N N N N N N N N N N N N N N N N




c. We define an agent as an entity that takes action in response to
N N N N N N N N N N N N




percepts from an envi- ronment.
N N N N N




d. We define rationality as the property of a system which does the
N N N N N N N N N N N N N N N N N N N N N N




―right thing‖ given what it knows.
N See Section 2.2 for a more N N N N N N N N N N N N




complete N discussion. The basic concept is perfect rationality; N N N N N N N N N N N N N N




Section N




?? describes the impossibility of achieving perfect rational- ity and
N N N N N N N N N




proposes an alternative definition.
N N N N




e. We define logical reasoning as the a process of deriving new
N N N N N N N N N N N N N N N N N N N N




sentences from old, such that the new sentences are necessarily true
N N N N N N N N N N N N




if the old ones are true. (Notice that does not refer to any specific
N N N N N N N N N N N N N N N N




syntax or formal language, but it does require a well-defined notion
N N N N N N N N N N N




of truth.)
N N




© 2023 Pearson Education, Hoboken, NJ.All rights reserved.
N N N N N N N N




Exercise 1.1.#TURI N




Read Turing‘s original paper on AI (Turing, 1950). In the paper, he discusses several
N N N N N N N N N N N N N




objectionstohisproposedenterpriseandhistestforintelligence.Whichobjectionsstillcarry
N N N N N N N N N N N N N N