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.
Introduction
Intelligent Agents
Solving Problems by Searching
Search in Complex Environments
Adversarial Search and Games
Constraint Satisfaction Problems
Logical Agents
First-Order Logic
Inference in First-Order Logic
Knowledge Representation
Automated Planning
Quantifying Uncertainty
Probabilistic Reasoning
Probabilistic Reasoning over Time
Probabilistic Programming
Making Simple Decisions
Making Complex Decisions
Multiagent Decision Making
Learning from Examples
Learning Probabilistic Models
Deep Learning
Reinforcement Learning
Natural Language Processing
Deep Learning for Natural Language Processing
Robotics
Philosophy and Ethics of AI
The Future of AI
