In many applications, black-box prediction is not satisfactory, and understanding the data is
of critical importance. Typically, approaches useful for understanding of data involve logical …

Automatic pattern recognition is usually considered as an engineering area which focusses
on the development and evaluation of systems that imitate or assist humans in their ability of …

E-mail: duch@ phys. uni. torun. pl Abstract. One of the biggest challenges of science today is
to outline connections between the subjective world of human experience, as studied by …

While neural networks are widely applied as powerful tools for inductive learning of
map**s in domains of fixed-length feature vectors, there are still expressed principled …

Partitioning a data set of attributed graphs into clusters arises in different application areas of
structural pattern recognition and computer vision. Despite its importance, graph clustering …

Cognitive Informatics (CI) is a contemporary multidisciplinary field spanning across
computer science, information science, cognitive science, brain science, intelligence …

We outline a formal foundation for a “structural”(or “symbolic”) object/event representation,
the necessity of which is acutely felt in all sciences, including mathematics and computer …

Regularities in the world are human defined. Patterns in the observed phenomena are there
because we define and recognize them as such. Automatic pattern recognition tries to …

Numbers have emerged historically as the most popular/convenient form of representation,
and the basic scientific paradigm is built on the foundation of numeric, or quantitative …

In spite of the fact that some of the outstanding physiologists and neurophysiologists (eg
Hermann von Helmholtz and Horace Barlow) insisted on the central role of inductive …