The broader scope of our investigations is the search for the way in which concepts and their combinations carry and influence meaning and what this implies for human thought. More specifically, we examine the use of the mathematical formalism of quantum mechanics as a modeling instrument and propose a general mathematical modeling scheme for the combinations of concepts. We point out that quan...

Learning algorithms typically model the acquisition of conceptual knowledge from some start state to some fixed learned end state. Natural associative learning demonstrates a more comprehensive range of processes which complement this static view of learning. An experimental regimen is presented for evaluating learning algorithms against this wider remit. This approach provides a general basis ...

AbsfructWe propose a self-organizing neural structure with dynamic and spatial changing weights for a feature space representation of concept formation. An essential core of this self-organization is based on an Unsupervised learning with incomplete information for the dynamic changing and an extended Hebbian rule for the spatial changing. A concept formation problem requires the neural network...

This paper describes a successful approach to concept learning for heuristic classi cation. Almost all current programs for this task create or use explicit, abstract generalizations. These programs are largely ine ective for domains with weak or intractable theories. An exemplar-based approach is suitable for domains with inadequate theories but raises two additional problems: determining simi...

The main interest of this research is to discover clinical implications from a large PTCA (Percutaneous Transluminal Coronary Angioplasty) database. A case-based concept formation model D-UNIMEM, modified from Lebowitz's UNIMEM, is proposed for this purpose. In this model, we integrated two kinds of class membership and the index-conjunction class membership. The former is a polythetic clusteri...

Machine learning is the key to text classification, a granular computing approach to machine learning is applied to learning classification rules by considering the two basic issues: concept formation and concept relationships identification. In this paper, we concentrate on the selection of a single granule in each step to construct a granule network. A classification rule induction method is ...

By a normative system jurists often mean the law of a country, like Swedish law, or part of the law of a country, such as the Swedish law of contracts. With regard to the issue how a logical reconstruction of a normative system should be made, a central question is what kind of entities a normative system is composed of and how it should be represented. The aim of the present paper is to contri...

In this article, we consider contemporary theories of concepts, and Bayesian and self-organizing models of concept formation. After introducing the different models, we present our own experiment. It utilizes a multi-agent simulation framework, in which the emergence of a common vocabulary can be studied. In the experiment, we use jointly the self-organizing maps and probabilistic modeling of c...