This paper describes a system named AAl (Articulation Aid 1) which aids human users in the formation of new concepts in the domain of engineering and science. From the viewpoint of concept formation, one main process of creation is divergent thinking in which broad alternatives are searched, and another process is convergent thinking in which a unique solution is sought. From the viewpoint of h...

We argue that visual, analogical representations of mathematical concepts can be used by automated theory formation systems to develop further concepts and conjectures in mathematics. We consider the role of visual reasoning in human development of mathematics, and consider some aspects of the relationship between mathematics and the visual, including artists using mathematics as inspiration fo...

This paper presents how a situated agent model can wrap around a design optimization tool and construct concepts from interaction between the agent, the design problem and the use of the tool. The agent develops its structure and behaviour specific to what it is confronted with – its experience. As a consequence, designers can integrate their expertise with the learning results from the agent t...

Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the problem of knowledge acquisition for knowledge-based systems. In this paper we have described INC, a program that generates a hierarchy of concept descriptions incrementally. INC searches a space of classification hier...

We propose a method to incrementally compute and use, during the concept formation, the relevance of a concept property. This relevance is computed through the account of the property correlation with other ones and it is used by the concept quality function in order to improve predictive accuracy. The proposed approach is analyzed concerning both the prediction power of the generated concepts ...

Categorisation and classification are areas that have been well studied in machine learning. However, the use of cognitive theories in psychology as a basis to implement a category formation system designed for creative purposes and based on human behaviour is still largely unexplored. Our aim in this project is to verify how some of the ideas on uncertainty and ambiguity in classification coul...

We describe ARACHNE, a concept formation system that, uses explicit constraints on tree structure and local restructuring operators to produce well-formed probabilistic concept trees. We also present a quantitative measure of tree quality and compare the system's performance in artificial and natural domains to that of COBWEB, a well-known concept formation algorithm. The results suggest that A...

This paper proposes an a l t e r n a t i v e to Quin lan 's a lgor i thm fo r forming c l a s s i f i c a t i o n t rees from large sets of examples. My a lgor i thm is guaranteed to te rminate . Quin lan 's a lgor i thm i s usua l ly f a s t e r . I. The Nature of the Problem. We have a populat ion of objects which we want to c l a s s i f y i n to two** groups. We have a set of a t t r i b u ...

This paper describes an approach to software reuse that involves generating and retrieving abstractions from existing software systems using concept formation methods. The potential of the approach is illustrated through two important activities of the reuse process. First, the concept hierarchy generated by the concept formation methods is used for organizing and retrieving the artifacts insid...