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Gaschnig, J.
Application of the PROSPECTOR system to geological exploration problems
Gaschnig, J.
A practical criterion for the success of a knowledge-based problem-solving system is its usefulness as a tool to those working in its specialized domain of expertise. This paper describes an evaluation and several applications of a knowledge-based system, the PROSPECTOR consultant for mineral exploration. PROSPECTOR is a rule-based judgmental reasoning system that evaluates the mineral potential of a site or region with respect to inference network models of specific classes of ore deposits. Knowledge about a particular type of ore deposit is encoded in a computational model representing observable geological features and the relative significance thereof.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.
Model design in the PROSPECTOR consultant system for mineral exploration
Duda, R. | Gaschnig, J. | Hart, P.E.
D.Michie (Ed.), Expert systems in the micro- electronic age.Edinburgh: Edinburgh University Press, 153-167
Performance measurement and analysis of certain search algorithms
Gaschnig, J.
I will remain Ion8 and deeply indebted to Herb Simon, H. T. Kung, AI Newell, Jay
Exactly how good are heuristics? Toward a realistic predictive theory of best-first search
Gaschnig, J.
Also found at aminer.orgProc. IJCAI 77 VOL 1 MASSACHUSETTS INSTITUTE OF TECHNOLOGY CAMBRIDGE, MASSACHUSETTS, USA AUGUST 22 - 25 , 1977, pp.434-441.
A general backtrack algorithm that eliminates most redundant tests
Gaschnig, J.
In IJCAI-77, p. 457.