A thorough introduction to artificial intelligence (AI), this text provides a comprehensive and in-depth overview of the key concepts and techniques in AI. It also discusses the various areas and successes of the rational and emergent software approaches to AI. Throughout the text, theory is introduced via examples, giving readers the foundation to solve problems with logic that they can use later in AI-related research and other domains. The author also covers algorithms in sufficient detail, allowing readers to readily understand and implement them.

Author Biography

Richard E. Neapolitan is a professor of computer science at Northeastern Illinois University. Dr. Neapolitan has published in prestigious journals related to reasoning under uncertainty and has authored five books: Probabilistic Reasoning in Expert Systems, Learning Bayesian Networks, Foundations of Algorithms, Probabilistic Methods for Financial and Marketing Informatics, and Probabilistic Methods for Bioinformatics. His research interests include probability and statistics, expert systems, cognitive science, and applications of probabilistic modeling to fields such as medicine, biology, and finance. Xia Jiang is an assistant professor in the Department of Biomedical Informatics at the University of Pittsburgh. Dr. Jiang co-authored Probabilistic Methods for Financial and Marketing Informatics. Her current research focuses on developing novel algorithms/systems that improve the computational efficiency of large data analysis and network modeling of cancer genome data.