Latest Resources

Most Popular

Artificial Intelligence Books, Documents, and Lectures

Title	Year	Description
A Brief Introduction to Genetic Algorithms	2002	A brief introduction to Genetic Algorithms
A Field Guide to Genetic Programming	2008	The Field Guide is a clear and concise introduction and reference to all things genetic programming related.
A Genetic Algorithm Tutorial	2006	This tutorial covers the canonical genetic algorithm as well as more experimental forms of genetic algorithms.
Gaussian Processes for Machine Learning	2006	The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms.
Introduction to Machine Learning	1996	The author's intention in this book is to pursue a middle ground between a theoretical text book and one that focuses on applications. The book concentrates on the important ideas in machine learning.
Machine Learning, Neural and Statistical Classification	1994	The aim of this book is to provide an up-to-date review of different approaches to classification, compare their performance on a wide range of challenging data-sets, and draw conclusions on their applicability to realistic industrial problems.
Machine Perception	1982	A book based on the the author's experiencing teaching graduate courses on machine perception.
Machine Vision: Automated Visual Inspection and Robot Vision	1991	A book aiming to providing the reader with a solid grounding in the fundamental tools for image acquisition, processing, and analysis.
Planning Algorithms	2006	This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics.
Practical Artificial Intelligence Programming in Java	2005	Written in the "cookbook" style, this book discusses search algorithms, natural language processing, expert systems, genetic algorithms, neural networks, machine learning, statistical natural language processing and spam email detection.
Reinforcement Learning: An Introduction	1998	This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning.
Uni-Processor Genetic Algorithm		UGA is an object oriented genetic algorithm package developed by Martin Smith. It implements a multi-population GA on a single processor. In addition there are extensive class libraries which facilitate the development of genetic algorithm.