Artificial Intelligence: A Modern Approach eBook (4e) : 9780134671932

Artificial Intelligence: A Modern Approach eBook (4e)

Russell,S et al
Published by
Pearson Higher Ed USA
Title type
NZ/Pacific customers only
This eText can only be purchased by people residing in New Zealand, Fiji, Samoa, Tonga or Cook Islands with a credit card from the same country. Click here to find the Pearson website for your region.

The most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence

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.

Digital Access Code: When you buy an eBook you will receive an email with your unique redemption code code. Simply go to VitalSource Bookshelf to download the FREE Bookshelf software. After installation, enter your redemption code for your eBook.

Please note: eBooks are available for download immediately and cannot be returned once purchased.

The full text downloaded to your computer. With VitalSource eBooks you can:

  • search for key concepts, words and phrases
  • make highlights and notes as you study
  • share your notes with friends

The eBook is downloaded to your computer and accessible either offline through the VitalSource Bookshelf, available online and also via the iPad/Android app.

Time Limit: This VitalSource eBook does not have an expiry date. You will continue to access your eBook whilst you have your VitalSource Bookshelf installed.

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
Features & benefits
  • Nontechnical learning material introduces major concepts using intuitive explanations, before going into mathematical or algorithmic details. The nontechnical language makes the book accessible to a broader range of readers.
  • A unified approach to AI shows students how the various subfields of AI fit together to build actual, useful programs.
  • The basic definition of AI systems is generalised to eliminate the standard assumption that the objective is fixed and known by the intelligent agent; instead, the agent may be uncertain about the true objectives of the human(s) on whose behalf it operates.
  • 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.
  • Stay current with the latest technologies and present concepts in a more unified manner
  • New chapters feature expanded coverage of probabilistic programming (Ch. 15); multiagent decision making (Ch. 18 with Michael Wooldridge); deep learning (Ch. 21 with Ian Goodfellow); and deep learning for natural language processing (Ch. 24 with Jacob Devlin and Mei-Wing Chang).
  • Increased coverage of machine learning.
  • Significantly updated material on robotics includes robots that interact with humans and the application of reinforcement learning to robotics.
  • New section on causality by Judea Pearl.
  • New sections on Monte Carlo search for games and robotics.
  • New sections on transfer learning for deep learning in general and for natural language.
  • New sections on privacy, fairness, the future of work, and safe AI.
  • Extensive coverage of recent advances in AI applications.
  • Revised coverage of computer vision, natural language understanding, and speech recognition reflect the impact of deep learning methods on these fields.
Access Code info.

To get the most out of your eBook you need to download the VitalSource Bookshelf software. This software is free to download and use. View the VitalSource Bookshelf system requirements here.

Download Information: Once purchased, you can view and/or download your eBook instantly, either via the download link which you will receive as soon as you complete your online order or by viewing the download link against the order in the My Account area of this website.

Please note: eBooks are available for download immediately and cannot be returned once purchased.