this paper assumes the cell formation problem as a distributed decision network. it proposes an approach based on application and extension of information theory concepts, in order to analyze informational complexity in an agent- based system, due to interdependence between agents. based on this approach, new quantitative concepts and definitions are proposed in order to measure the amount of t...

Many existing approaches for measuring text complexity tend to overestimate the complexity levels of informational texts while simultaneously underestimating the complexity levels of literary texts. We present a two-stage estimation technique that successfully addresses this problem. At Stage 1, each text is classified into one or another of three possible genres: informational, literary or mix...

It is well-known that enzymes is very important as reaction factor in life systems activity. But the properties based on information theory are not yet enough in biological studies. Then, we examined correlation the complexity at amino acid sequences with its function of Enzymes by informational measure, in order to elucidate the informational properties of sequence structure. Also, power spect...

This thesis attempts to quantify the amount of information needed to learn certain tasks. The tasks chosen vary from learning functions in a Sobolev space using radial basis function networks to learning grammars in the principles and parameters framework of modern linguistic theory. These problems are analyzed from the perspective of computational learning theory and certain unifying perspecti...

This paper assumes the cell formation problem as a distributed decision network. It proposes an approach based on application and extension of information theory concepts, in order to analyze informational complexity in an agent- based system, due to interdependence between agents. Based on this approach, new quantitative concepts and definitions are proposed in order to measure the amount of t...