Artificial Intelligence: A Modern Approach, 4e

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NPR 1,541.00


Artificial Intelligence: A Modern Approach, 4e

The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI).

NPR 1,541.00 1541.0 NPR NPR 1,712.00

NPR 1,712.00


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  • Pages
  • Pages 1292
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Artificial Intelligence: A Modern Approach, 4e

The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multiagent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.

Features
  • Nontechnical learning material introduces major concepts using intuitive explanations, before going into mathematical or algorithmic details.
  • A unified approach to AI shows students how the various subfields of AI fit together to build actual, useful programs.
  • In-depth coverage of both basic and advanced topics provides students with a basic understanding of the frontiers of AI without compromising complexity and depth.
  • NEW - New chapters feature expanded coverage of probabilistic programming; multiagent decision making; deep learning; and deep learning for natural language processing.
Contents: 

1. Introduction
2. Intelligent Agents
3. Solving Problems by Searching
4. Search in Complex Environments
5. Constraint Satisfaction Problems
6. Adversarial Search and Games
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. Making Simple Decisions
16. Making Complex Decisions
17. Multiagent Decision Making
18. Learning from Examples
19. Knowledge in Learning
20. Learning Probabilistic Models
21. Deep Learning
22. Reinforcement Learning
23. Natural Language Processing
24. Deep Learning for Natural Language Processing
25. Robotics
26. Computer Vision
27. Philosophy and Ethics of AI
28. Future of AI

Book
Author Russell
Pages 1292
Year 2022
ISBN 9789356063570
Publisher Pearson
Language English
Uncategorized
Subject Computer Science / Artificial Intelligence (AI)
Edition 4/e
Weight 4.17 kg
Dimensions 20.3 x 25.4 x 4.7 cm
Binding Paperback
Length (cm) 20.3
Width (cm) 25.4
Height (cm) 4.7