A decision may be difficult because complex information processing is required to evaluate choices according to deterministic decision rules and/or because it is not certain which choice will lead to the best outcome in a probabilistic context. Factors that tax decision making such as decision rule complexity and low decision certainty should be disambiguated for a more complete understanding o...

A fuzzy preference relation is a powerful and popular model to represent both individual and group preferences and can be a basis for decision-making models that in general provide as a result a subset of alternatives that can constitute an ultimate solution of a decision problem. To arrive at such a Þnal solution individual and/or group choice rules may be employed. There is a wealth of such r...

Each semester, students go through the process of selecting appropriate courses. It is difficult to find information about each course and ultimately make decisions. The objective of this paper is to design a course recommender model which takes student characteristics into account to recommend appropriate courses. The model uses clustering to identify students with similar interests and skills...

Decision mining enriches process models with rules underlying decisions in processes using historical process execution data. Choices between multiple activities are specified through rules defined over process data. Existing decision mining methods focus on discovering mutually-exclusive rules, which only allow one out of multiple activities to be performed. These methods assume that decision ...

Many different rules for decision making have been introduced in the literature. We show that a notion of generalized expected utility proposed in a com­ panion paper [Chu and Halpern, 2003] is a univer­ sal decision rule, in the sense that it can represent essentially all other decision rules.

As options models move from financial markets to corporate decision making, it is fitting to question the simple domain extension of option pricing theory by considering behavioral decision-making biases. We suggest, however, that, given the negative evolutionary consequences of ignoring optionlike investments, organizations invent heuristic rules to counter these biases. We propose the idea of...

Uncertain and stochastic states have been always taken into consideration in the fields of risk management and accident, like other fields of industrial engineering, and have made decision making difficult and complicated for managers in corrective action selection and control measure approach. In this research, huge data sets of the accidents of a manufacturing and industrial unit have been st...