Artificial Intelligence 4th Edition Russell Solution Manual
Solution Manual for Artificial Intelligence A Modern Approach 4th Edition By Stuart Russell, Peter Norvig, ISBN-13: 9780134610993
Table of Contents
1. Introduction
2. Intelligent Agents
3. Solving Problems by Searching
4. Search in Complex Environments
5. Adversarial Search and Games
6. Constraint Satisfaction Problems
7. Logical Agents
8. First-Order Logic
9. Inference in First-Order Logic
10. Knowledge Representation
11. Automated Planning
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
19. Learning from Examples
20. Learning Probabilistic Models
21. Deep Learning
22. Reinforcement Learning
23. Natural Language Processing
24. Deep Learning for Natural Language Processing
25. Robotics
26. Philosophy and Ethics of AI
27. The Future of AI
1.1 What Is AI?
Exercise 1.1.#DEFA
Define in your own words: (a) intelligence, (b) artificial intelligence, (c) agent, (d) rationality,
(e) logical reasoning.
a. Dictionary definitions of intelligence talk about “the capacity to acquire and apply
knowledge” or “the faculty of thought and reason” or “the ability to comprehend and
profit from experience.” These are all reasonable answers, but if we want something
quantifiable we would use something like “the ability to act successfully across a wide
range of objectives in complex environments.”
b. We define artificial intelligence as the study and construction of agent programs that
perform well in a given class of environments, for a given agent architecture; they do
the right thing. An important part of that is dealing with the uncertainty of what the
current state is, what the outcome of possible actions might be, and what is it that we
really desire.
c. We define an agent as an entity that takes action in response to percepts from an environment.
