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.
Overview of the book:
The main unifying theme is the idea of an intelligent agent. We define AI as the study of
agents that receive percepts from the environment and perform actions. Each such agent
implements a function that maps percept sequences to actions, and we cover different ways
to represent these functions, such as reactive agents, real-time planners, decision-theoretic
systems, and deep learning systems. We emphasize learning both as a construction method
for competent systems and as a way of extending the reach of the designer into unknown
environments. We treat robotics and vision not as independently defined problems, but as
occurring in the service of achieving goals. We stress the importance of the task
environment in determining the appropriate agent design.