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Principles of artificial intelligence
A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used. Palo Alto, California: Tioga.
Problem solving applied to natural language generation
This research was supported at SRI International by the Defense Advanced Research Projects Agency under contract N00039--79--C--0118 with the Naval Electronic Systems Command. The views and conclusions contained in this document are those of the author and should not be interpreted as representative of the official policies either expressed or implied of the Defense Advanced Research Projects Agency, or the U. S. Government. The author is grateful to Barbara Grosz, Gary Hendrix and Terry Winograd for comments on an earlier draft of this paper.
An analysis of minimax
In Clarke, M. R. B. (Ed.), Advances in Computer Chess 2, pp. 103-109. Edinburgh University Press
An analysis of minimax
In Clarke, M. R. B. (Ed.), Advances in Computer Chess 2, pp. 103-109. Edinburgh University Press
The HEARSAY-II speech understanding system: Integrating knowledge to resolve uncertainty
ACM Computing Survey 12:213-253
A deductive approach to program synthesis
ACM Transactions on Programming Languages and Systems 2(1): 90-121.
Consultation systems for physicians
Proc. Canadian Soc. for Computational Studies of Intelligence, Univ. Victoria, Victoria, BC (1980)
Using patterns and plans in chess
Earlier version in IJCAI 6 (1979). Artificial Intelligence, 14 (2), 165-203.
An investigation of computer coaching for informal learning activities
Computer-based tutoring/coaching systems have the promise of enhancing the educational value of gaming environments by guiding a student's discovery learning. This paper provides an in-depth view of (i) the philosophy behind such systems, (ii) the kinds of diagnostic modeling strategies required to infer a student's shortcomings from observing his behavior and (iii) the range of explicit tutorial strategies needed for directing the Tutor to say the right thing at the right time. Examples of these issues are drawn for a computer-based coaching system for a simple game-How the West was Won. Our intention in writing this paper is to make explicit the vast amounts of tutorial knowledge required to construct a coaching system that is robust, friendly and intelligent enough to survive in home or classroom use. During the past three years, we have witnessed how subtle the computer-based coaching problem really is.