Knowledge discover in Data bases (KDD) concerns the development of models which allow the representation and organization of the knowledge hidden in data. Machine learning systems are an alternative to automate the KDD process. In particular, incremental concept formation systems construct hierarchical abstract representations from observations (non-classified description of specific entities, ...

When faced with a complex task, humans often identify domain-specific concepts that make the task more tractable. In this thesis, I investigate the formation of domain-specific concepts of this sort. I propose a set of principles for formulating domain-specific concepts, including a new inductive bias that I call the equivalence class principle. I then use the domain of two-player, perfect-info...

This paper presents a computationally tractable view on where simple design concepts come from by proposing a paradigm for the formation of design concepts based on the emergence of patterns in the representation of designs. It is suggested that these design patterns form the basis of concepts. These design patterns once learned are then added to the repertoire of known patterns so that they do...

A model for the formation of situation concepts is described. A characteristic of this form of concept formation is that it does not require instructive feedback. This renders it suitable for concept formation by autonomous agents. It is experimentally demonstrated that situation concepts constructed independently by several agents can convey useful information between agents through a learned ...

We develop a model of void formation, which simulates the evolution of voids from the moment of the last scattering until the present instant. We find that in order to obtain a model which would be fully consistent with the observational constraints the existence of radiation must be taken into account. The ratio of radiation energy density to matter energy density in CDM models at the moment o...

A central challenge for any theory of concept learning comes from Fodor's argument against the learning of concepts, which lies at the basis of contemporary computationalist accounts of the mind. Robert Goldstone and his colleagues propose a theory of perceptual learning that attempts to overcome Fodor's challenge. Its main component is the addition of a cognitive device at the interface of per...

We advance a dominant neural strategy for facilitating conceptual thought. Concepts are groupings of "object" attributes. Once the brain learns such critical groupings, the "object" attributes are inhibited from conscious awareness. We see the whole, not the parts. The details are inhibited when the concept network is activated, ie. the inhibition is dynamic and can be switched on and off. Auti...

International attention is currently focused on alleviating health disparities through the adoption of new paradigms of research and the development of culturally relevant theories of health and illness. Yet, in spite of consistent calls to inform these deficiencies, the methodological trajectory from problem identification to theoretical development has remained relatively elusive. In this art...