Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision mak...
Many-objective problems are difficult to solve using conventional multi-objective evolutionary algorithms (MOEAs) as these algorithms rely primarily on Pareto ranking to guide the ...
Today there are numerous tools for decision analysis, suitable both for human and artificial decision makers. Most of these tools require the decision maker to provide precise num...
Scheduling problems overall assume that it is possible to identify stable criteria definitions measuring the quality of alternatives. In real world problems however, this does not ...
In Multiple Criteria Decision Analysis, the preferences of the decision maker regarding each criterion are classically modelled by a utility function depending on one single varia...
Abstract. We consider a control problem where the decision maker interacts with a standard Markov decision process with the exception that the reward functions vary arbitrarily ove...
We consider the following setting: a decision maker must make a decision based on reported data points with binary labels. Subsets of data points are controlled by different selfi...
Reshef Meir, Ariel D. Procaccia, Jeffrey S. Rosens...
: AHP is proposed to give the importance grade with respect to many items. The comparison value that is the element of a comparison matirx is used to be crisp, however, it is easy ...
The effective management of knowledge is critical for organizations that are striving to gain or maintain a competitive advantage and that are in the process of re-structuring for...
Abstract. This paper discusses how preference information of the decision maker can in general be integrated into multiobjective search. The main idea is to first define the opti...