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Creator:: Flann, Nicholas S. and Dietterich, Thomas G.
Abstract:: This technical report reprints two articles that appeared in Proceedings of the Third International Machine Learning Workshop at Skytop, Pennsylvania, June 24-26, 1985. The first paper, The EG Project: Recent Progress, summarizes work on the EG project, which is investigating the role of active experimentation in aiding machine learning programs....
Resource Type:: Technical Report
Full Text:: . Flann and Thomas G. Dietterich Department of Computer Science Oregon State University Corvallis

Creator:: Dietterich, Thomas G. and Flann, Nicholas S.
Resource Type:: Technical Report
Full Text:: Problem 88-30-2 Thomas G. Dietterich Nicholas S. Flann Department of Computer Science Oregon State

Creator:: Flann, Nicholas S. and Dietterich, Thomas G.
Abstract:: This paper formalizes a new learning from examples problem: identifying a correct concept definition from positive examples such that the concept is some specialization of a target concept defined by a domain theory. This paper describes an empirical study that evaluates three methods for solving this problem: explanation based generalization...
Resource Type:: Technical Report
Full Text:: -Based Methods for I~ductive Learning Nicholas S. Flann Thomas G. Dietterich Department of Computer

Creator:: Flann, Nicholas S. and Dietterich, Thomas G.
Abstract:: We introduce five criteria by which to judge the suitability of a method for solving the problem of learning concepts from examples: correctness (the correct concept should be identified), performance efficiency (the learned definition should be efficient to apply to the performance task), flexibility (the method should be able to...
Resource Type:: Technical Report
Full Text:: Method that Exploits Do~ain Knowledge to Learn from Examples Nicholas S. Flann Thomas G. Dietterich

Creator:: Flann, Nicholas S. and Dietterich, Thomas G.
Abstract:: The task of inductive learning from examples places constraints on the representation of training instances and concepts. These constraints are different from, and often incompatible with, the constraints placed on the representation by the performance task. This incompatibility explains why previous researchers have found it so difficult to construct good...
Resource Type:: Technical Report
Full Text:: REPRESENTATIONS FOR LEARNING FROM EXAMPLES Nicholas S. Flann Thomas G. Dietterich Department of Computer

Creator:: Dietterich, Thomas G., Flann, Nicholas S., and Wilkins, David C.
Abstract:: This report reviews the 31 papers on machine learning that were presented at the Ninth International Joint Conference on Artificial Intelligence (IJCAI-85) held in Los Angeles during August, 1985. The papers are grouped according to a taxonomy of the various subareas of machine learning research. The areas receiving the most...
Resource Type:: Technical Report
Full Text:: From IJCAI-85 Thomas G. Dietterich and Nicholas S. Flann Department of Computer Science Oregon

Creator:: Flann, Nicholas S., Dietterich, Thomas G., and Corpron, Dan R.
Abstract:: Two powerful reasoning tools have recently appeared, logic programming and assumption based truth maintenance systems (ATMS). An ATMS offers significant advantages to a problem solver: assumptions are easily managed and the search for solutions can be carried out in the most general context first and in any order. Logic programming...
Resource Type:: Technical Report
Full Text:: LOGIC PROGRAMMING WITH THE ATMS Nicholas S. Flann Thomas G. Dietterich Dan R. Corpron Department

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