Empirical Methods in Artificial Intelligence: A Review
Paul Cohen's book Empirical Methods for Artificial Intelligence aims to encourage this trend by providing AI practitioners with the knowledge and tools needed for careful empirical evaluation. The volume provides broad coverage of experimental design and statistics, ranging from a gentle introduction of basic ideas to a detailed presentation of advanced techniques, often combined with illustrative examples of their application to the empirical study of AI. The book is generally well written, clearly organized, and easy to understand; it contains some mathematics -- but not enough to overwhelm readers. Examples come from AI work on planning, machine learning, natural language, and diagnosis.
Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.