@ARTICLE { Rsds3599,
author = {Nguyen, Hung T.}, 
title = {Some mathematical structures for computational information}, 
journal = {Information Sciences: An International Journal}, 
number = 	{(no. 1-2)}, 
volume = 128, 
pages = {67-89}, 
publisher = {Elsevier Science Inc.}, 
address = {Amsterdam, The Netherlands}, 
month = {September}, 
year = 2000, 
issn = {0020-0255}, 
abstract = {This paper is about the basic underlying mathematical structures of various types of imprecise information. Set theory and probability measures are basic ingredients in extracting some specific type of information and in reasoning with uncertain knowledge. But in this era of information technology, it is desirable to consider also more complex types of information, for example, information coming from human perception (see e.g., L.A. Zadeh, IEEE Trans. Circuits and Systems 45 (1) (1999) 105-119). As a first approximation, the classical ingredients could be generalized to adequately model new types of information. As such, we will describe in this paper four types of non-classical sets, namely random sets, rough sets, conditional sets and fuzzy sets, as well as their associated non-additive measures.}, 
keywords = {capacities, conditional events, fuzzy logic, random sets, rough sets, }, 
}