The information-theoretical entropy is an effective measure of uncertainty connected with an information source. Its transfer from the classical probabilistic information theory models to the fuzzy set theoretical environment is desirable and significant attempts were realized in the existing literature. Nevertheless, there are some open topics for analysis in the suggested models of fuzzy entropy - the main of them regard the formal aspects of the fundamental concepts. Namely their rather additive (i. e., probability-like) than monotonous (typical for fuzzy set theoretical models) structure. The main goal of this paper is to describe briefly the existing state of art, and to suggest and analyze alternative, more fuzzy set theoretical, approaches to the fuzzy entropy developed as a significant characteristic of the information sources, in the information-theoretical sense.
The measurement of information emitted by sources with uncertainty of random type is known and investigated in many works. This paper aims to contribute to analogous treatment of information connected with messages from other uncertain sources, influenced by not only random but also some other types of uncertainty, namely with imprecision and vagueness. The main sections are devoted to the characterization and quantitative representation of such uncertainties and measures of information produced by sources of the considered type.