The decision theory is defined typically as the combination of utility theory and probability theory. In this paper we generalize the decision theory as the performance measure theory and uncertainty theory. Intelligent agents look for approximate optimal decisions under bounded resources and uncertainty. The $-calculus process algebra for problem solving applies the cost performance measures t...

In the paper we consider non-Archimedean fuzziness and probabilities. The idea of non-Archimedean multiple-validities is that (1) the set of values for the vagueness and probability is uncountable infinite and (2) this set is not wellordered. For the first time the non-Archimedean logical multiple-validity was proposed in [13], [14]. We propose non-Archimedean fuzziness that is defined on an in...

data envelopment analysis (dea) is a method to measure relative efficiency of a set of decision-making units (dmus) which uses multiple inputs and produces multiple outputs. in the conventional dea, crisp inputs and outputs are fundamentally necessary. but the observed values of inputs and outputs in real-world problems are sometimes imprecise. thus, performance measurement often needs to be do...

driven precast reinforced concrete piles (dprcp) is extensively used as a foundation for bridges constructed over canals in egypt in order to avoid the diversion of water canals. the objectives of this research include identifying the main activities of dprcp execution in the bridge-construction industry in egypt and the risk factors affecting them. in addition, assessment of the effects of the...

Markov chains (MCs) are widely used to model a great deal of financial and actuarial problems. Likewise, they also in many other fields ranging from economics, management, agricultural sciences, engineering or informatics medicine. This paper focuses on the use MCs for design non-life bonus-malus systems (BMSs). It proposes quantifying uncertainty transition probabilities BMSs by using fuzzy nu...

We introduce the fuzzy measure as a unifying structure for modeling knowledge about an uncertain variable. We show that a large class of well established types of uncertainty representation can be modeled in this framework. A measure of entropy associated with a fuzzy measure is introduced and its manifestation for different fuzzy measures is described. The problem of uncertain decision making ...