Synopsis
The broad range of material included in these volumes suggests to the newcomer thenature of the field of artificial intelligence, while those with some background in AI willappreciate the detailed coverage of the work being done at MIT. The results presented are related tothe underlying methodology. Each chapter is introduced by a short note outlining the scope of theproblem begin taken up or placing it in its historical context.
Contents, VolumeI: Expert Problem Solving: Qualitative and Quantitative Reasoning in Classical Mechanics; ProblemSolving About Electrical Circuits; Explicit Control of Reasoning; A Glimpse of Truth Maintenance;Design of a Programmer's Apprentice; Natural Language Understanding and Intelligent ComputerCoaches: A Theory of Syntactic Recognition for Natural Language; Disambiguating References andInterpreting Sentence Purpose in Discourse; Using Frames in Scheduling; Developing Support Systemsfor Information Analysis; Planning and Debugging in Elementary Programming; Representation andLearning: Learning by Creating and Justifying Transfer Frames; Descriptions and the Specializationof Concept; The Society Theory of Thinking; Representing and Using Real-World Knowledge.
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About the Authors
Patrick H. Winston is Professor of Electrical Engineering and Computer Science and Director of the Artificial Intelligence Laboratory at MIT.
Daniel G. Bobrow is a Research Fellow in the Intelligent Systems Laboratory, Xerox Palo Alto Research Center, editor-in-chief of the Journal of Artificial Intelligence, and Chair of the Governing Board of the Cognitive Science Society.
Michael Brady is Senior Research Scientist at MIT's Artifical Intelligence Laboratory.
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Artificial Intelligence: An MIT Perspective (vol. 1)
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Artificial Intelligence: An MIT Perspective Volume I: Expert Problem Solving. Natural Language Understanding. Intelligent Computer Coaches. Representation and Learning
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