This version of the book presents the changes that have occurred in AI since the previous edition in 2010, specifically:

• It focuses more on machine learning, due to the increased availability of data, computational resources, and new algorithms.
• It extensively covers the fields of deep learning, probabilistic programming, and multi-agent systems, each in a separate chapter.
• It revises the coverage of natural language understanding, robotics, and computer vision to reflect the impact of deep learning.
• In the robotics chapter, it now includes robots that interact with humans, as well as the application of reinforcement learning in robotics. In the previous edition, the goal of AI was defined as creating systems that attempt to maximize expected utility, where the specific utility information is provided by the system designers.

Now we no longer assume that the goal is fixed and known to the AI system; instead, the system may be uncertain about the true goals of the humans it is serving. It must learn what to maximize and operate correctly even when uncertain about the goal.
It covers in more detail the impact of AI on society, including vital issues of ethics, justice, trust, and safety. Overall, about 25% of the book's content is completely new. The remaining 75% has been extensively rewritten to present a more unified picture of the field. 22% of the references in this edition are works published from 2010 onwards.