Artificial Intelligence: A Modern Approach, 4th edition
$24.00
📚 Delivered within 24 hours via email Artificial Intelligence: A Modern Approach, 4th Edition, by Stuart Russell and Peter Norvig, is the definitive AI textbook. Used by more than 1,500 universities, it introduces major concepts using intuitive explanations and nontechnical language, before going into mathematical or algorithmic details. AI ethics and safety are integrated throughout, emphasizing responsible AI use.
With this trusted textbook, you’ll build a strong foundation in modern AI concepts, from search and optimization to constraint satisfaction, adversarial games, intelligent agents, planning, and logic and knowledge representation. You’ll then apply mathematical thinking as you explore machine learning, natural language processing, robotics, deep learning, probabilistic reasoning, and Bayesian networks.
The 4th Edition explores the latest technologies while presenting concepts more cohesively. New chapters expand on probabilistic programming, multiagent decision-making, deep learning, and deep learning for natural language processing. Revised coverage of computer vision, speech recognition, and natural language understanding reflects the growing impact of deep learning on these rapidly evolving fields.
Published by Pearson (December 21st 2021) – Copyright © 2022
ISBN-13: 9780137505135
Subject: Artificial Intelligence
Category: Introduction to Artificial Intelligence
Description
Table of Contents
- 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
