Artificial Intelligence at MIT, Vol. 1: Expanding Frontiers.

The broad range of material included in these volumes suggests to the newcomer the nature of the field of artificial intelligence, while those with some background in AI will appreciate the detailed coverage of the work being done at MIT. The results presented are related to the underlying methodology. Each chapter is introduced by a short note outlining the scope of the problem begin taken up or placing it in its historical context.

Contents, Volume I: Expert Problem Solving: Qualitative and Quantitative Reasoning in Classical Mechanics; Problem Solving About Electrical Circuits; Explicit Control of Reasoning; A Glimpse of Truth Maintenance; Design of a Programmer's Apprentice; Natural Language Understanding and Intelligent Computer Coaches: A Theory of Syntactic Recognition for Natural Language; Disambiguating References and Interpreting Sentence Purpose in Discourse; Using Frames in Scheduling; Developing Support Systems for Information Analysis; Planning and Debugging in Elementary Programming; Representation and Learning: Learning by Creating and Justifying Transfer Frames; Descriptions and the Specialization of Concept; The Society Theory of Thinking; Representing and Using Real-World Knowledge.

Understanding how the shape of a three-dimensional object may be recovered from shading in a tow-dimensional image of the object is one of the most important--and still unresolved--problems in machine vision. This book is the first to provide a comprehensive review of shape from shading. It brings together all of the seminal papers on the subject, shows how recent work relates to more traditional approaches, and provides a comprehensive annotated bibliography.