Artificial Intelligence: A Modern Approach, 4th Edition , Global Edition

Artificial Intelligence: A Modern Approach, 4th Edition , Global Edition | ISBN-13 9781292401171

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.

Product Description:

Explore the full landscape of Artificial Intelligence with the 4th Edition of Artificial Intelligence: A Modern Approach—the world’s most comprehensive and widely used AI textbook, written by Stuart Russell and Peter Norvig.

Whether you’re a student, educator, or tech professional, this industry-leading text provides a deep, structured, and cutting-edge approach to AI. Covering everything from problem-solving algorithms and machine learning to ethics, robotics, natural language processing, and deep learning, this global edition reflects the latest advancements in AI.

Newly updated with expanded chapters, mathematical rigor, and a companion site offering all exercises, this book provides a multi-faceted, modern view of AI in real-world applications—like autonomous robotics, decision-making systems, and digital assistants serving billions of users.

✅ Key Features:

• Explores AI fundamentals to advanced topics like POMDPs, probabilistic programming, deep learning, and transformers

• Includes modern tools & architectures: NLP with transformers, reinforcement learning, convolutional networks

• In-depth chapters on AI ethics, philosophy, and future applications

• Detailed appendices on math, probability, and algorithms

• Companion website with full exercises and resources

📚 What You’ll Learn:

🔹 Problem Solving & Search

Uninformed, heuristic, adversarial search, constraint satisfaction, and optimization.

🔹 Knowledge Representation & Planning

From logic and inference to hierarchical planning, uncertainty, and decision-making.

🔹 Machine Learning & Deep Learning

Covers supervised learning, neural networks, unsupervised learning, and ensemble methods.

🔹 Reinforcement Learning

Policy search, rewards-based systems, and real-world applications in robotics.

🔹 Natural Language Processing & Vision

NLP architectures, transformers, computer vision, perception, and robotics planning.

🔹 Ethics, Philosophy & Future of AI

Thoughtful coverage of AI safety, fairness, accountability, and human-robot interaction.

🧠 Chapters Overview (Selected):

• Introduction to AI and Intelligent Agents

• Problem Solving & Adversarial Search

• Knowledge Representation & Logic

• Reasoning under Uncertainty

• Machine Learning, Deep Learning, and Neural Networks

• Natural Language Processing & Computer Vision

• Robotics & Human-AI Interaction

• AI Ethics, Risks, and the Future

📌 Includes:

• Mathematical Background Appendix

• Algorithm & Language Notes

• Full Bibliography and Index

🎯 Perfect For:

• University AI courses (undergraduate & graduate level)

• Professionals working in AI, data science, or machine learning

• Researchers and developers exploring AI applications & ethics

• Anyone curious about how AI is shaping the present and future