The HR program forms concepts and makes conjectures in domains of pure mathematics and uses theorem prover OTTER and model generator MACE to prove or disprove the conjectures. HR measures properties of concepts and assesses the theorems and proofs involving them to estimate the interestingness of each concept and employ a best rst search. This approach has led HR to the discovery of interesting...

In inductive logic programming, concept formation in noisy domains can be considered as learning from noisy data. This paper describes an approach to learning from noisy examples with an approximate theory. Although this kind of learning is more close to practical application, there are few systems can deal with such problems. The proposed learning approach includes a theory preference criterio...

This article presents a series of experiments on concept formation. These experiments compared four different categorisation rules. The rules presume that the stimuli to be classified can be modelled psychologically as points in a dimensional space (Shepard 1987, Gärdenfors 1990a, 1990b). Two of the rules are based on the assumption that there are prototypical representatives of a concept, a th...

Recognizing the expressive power of graph representation and the ability of certain graph grammars to generalize, we attempt to use graph grammar learning for concept formation. In this paper we describe our initial progress toward that goal, and focus on how certain graph grammars can be learned from examples. We also establish grounds for using graph grammars in machine learning tasks. Severa...

6&. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION University of California (If applicable) U.S. Army Research Institute for at Irvine the Behavioral and Social Sciences 6c. ADDRESS (City, State, and ZIP Code) 7b. ADDRESS (City, State, and ZIP Code) Department of Information and Computer 5001 Eisenhower Avenue Science, University of California Alexandria, ...

Most empirical learning algorithms describe objects as a list of attribute-value pairs. A at attribute-value representation fails, however , to capture the internal structure of real objects. Mechanisms are therefore needed to represent the diierent levels of detail at which an object can be seen. A common structuring method is reviewed, and new principles of evaluation are proposed. As another...

Many interesting concepts in mathematics are essentially ‘cross-domain’ in nature, relating objects from more than one area of mathematics, e.g. prime order groups. These concepts are often vital to the formation of a mathematical theory. Often, the introduction of cross-domain concepts to an investigation seems to exercise a mathematician’s creative ability. The HR program, (Colton et al., 199...