"New to this edition:<p>This edition reflects the changes in AI since the last edition in 2010:<p>• We focus more on machine learning rather than hand-crafted knowledge engineering,
due to the increased availability of data, computing resources, and new algorithms.<p>• Deep learning, probabilistic programming, and multiagent systems receive expanded
coverage, each with their own chapter.<p>• The coverage of natural language understanding, robotics, and computer vision has
been revised to reflect the impact of deep learning.<p>• The robotics chapter now includes robots that interact with humans and the application
of reinforcement learning to robotics.<p>• Previously we defined the goal of AI as creating systems that try to maximize expected
utility, where the specific utility information—the objective—is supplied by the human
designers of the system. Now we no longer assume that the objective is fixed and known
by the AI system; instead, the system may be uncertain about the true objectives of the
humans on whose behalf it operates. It must learn what to maximize and must function
appropriately even while uncertain about the objective.<p>• We increase coverage of the impact of AI on society, including the vital issues of ethics,
fairness, trust, and safety.<p>• We have moved the exercises from the end of each chapter to an online site. This
allows us to continuously add to, update, and improve the exercises, to meet the needs
of instructors and to reflect advances in the field and in AI-related software tools.<p>• Overall, about 25% of the material in the book is brand new. The remaining 75% has
been largely rewritten to present a more unified picture of the field. 22% of the citations
in this edition are to works published after 2010."