Machine learning : an artificial intelligence approach - Anderson, John R. (John Robert), 1947-; Michalski, Ryszard S. (Ryszard Stanisaw), 1937-2007; Carbonell, Jaime G. (Jaime Guillermo); Mitchell, Tom M. (Tom Michael), 1951- (M. Kaufmann, 1983)
Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV and V discuss learning from observation and discovery, and learning from instruction, respectively. Part VI presents two studies on applied learning systems-one on the recovery of valuable information via inductive inference; the other on inducing models of simple algebraic skills from observed student performance in the context of the Leeds Modeling System (LMS).