Hallmark features of this title
- Nontechnical learning material introduces major concepts using intuitive explanations, before going into mathematical or algorithmic details. The nontechnical language makes this book accessible to a broader range of readers.
- A unified approach to AI clearly details how the various subfields of AI fit together to build actual, useful programs.
- In-depth coverage of both basic and advanced topics provides students with a solid understanding of the frontiers of AI without compromising complexity and depth.
- Copyright 2021
- Dimensions: 8" x 10"
- Pages: 1136
- Edition: 4th
- ISBN-10: 0-13-461099-7
- ISBN-13: 978-0-13-461099-3
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.
Table of Contents
Brief Table of Contents
- 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
- Philosophy and Ethics of AI
- The Future of AI