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Artificial intelligence
A modern approach
First published 1995 · 1232 pages
A monumental, intellectually rigorous journey through the architecture of machine intelligence and rational agency.
What it feels like
Reading this foundational text feels like being handed the blueprints to the modern digital world. It is a deeply cerebral and methodical experience, demanding focus but rewarding the reader with profound clarity. The atmosphere is scholarly and structured, guiding you step-by-step from basic problem-solving to the dizzying heights of probabilistic reasoning and neural networks. Despite its immense weight and academic rigor, the prose remains remarkably lucid, breaking down intimidating mathematical concepts with elegant analogies and logical precision. It is not a quick read, but rather a steady, intellectual climb. This is a book for engineers, computer scientists, and fiercely curious minds who want to move beyond the hype and truly understand the mechanics of artificial intelligence.
- Mood
- cerebral
- structured
- illuminating
- scholarly
- Tone
- authoritative
- academic
- clear
- objective
- rigorous
- Pace
- steady
- Themes
- the nature of intelligence · rational agency · computational problem solving · logic and probability · machine learning foundations
- The writing
- Precise, methodical, and surprisingly accessible, balancing dense mathematical theory with clear, practical analogies.
- The arc
- Moves from a daunting sense of complexity to a satisfying, structured mastery of intelligent systems.
- Who it's for
- Computer science students, engineers, and deeply curious minds seeking the definitive, rigorous foundation of artificial intelligence.
About the book
Intelligent Agents - Stuart Russell and Peter Norvig show how intelligent agents can be built using AI methods, and explain how different agent designs are appropriate depending on the nature of the task and environment. Artificial Intelligence: A Modern Approach is the first AI text to present a unified, coherent picture of the field. The authors focus on the topics and techniques that are most promising for building and analyzing current and future intelligent systems.
The material is comprehensive and authoritative, yet cohesive and readable. State of the Art - This book covers the most effective modern techniques for solving real problems, including simulated annealing, memory-bounded search, global ontologies, dynamic belief networks, neural networks, adaptive probabilistic networks, inductive logic programming, computational learning theory, and reinforcement learning.
Leading edge AI techniques are integrated into intelligent agent designs, using examples and exercises to lead students from simple, reactive agents to advanced planning agents with natural language capabilities.
Includes bibliographical references (p. 859-903) and index.
Description from Open Library.
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