Case-Based Reasoning [ai-cbr featured book]

Here you will find a regular featured book (which you can order online if you choose). We obviously will feature any new CBR books, but will also feature other books that will be of interest to you. These will include books on AI and machine learning, programming, the Internet and occasionally the odd book just for fun (we all need some down time).

Russell and Norvig's text book is a classic. If you haven't read it already you really ought to - then you'll discover where all the fuss about agents comes from.

Artificial Intelligence : A Modern Approach
(Prentice Hall Series in Artificial Intelligence) by Stuart J. Russell and Peter Norvig

order online now

This is a highly accessible, up-to-date professional reference for programmers, software engineers, system administrators, or technical managers, this book integrates state-of-the-art AI techniques into intelligent agent designs using examples and exercises to lead the reader from simple reactive agents to full knowledge-based agents with natural language capabilities.

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.