1. A method for supporting a decision making process, the method comprising: implementing a decision model for determining a solution to a decision problem based on attributes and uncertainties of the decision problem, the decision problem including information about a plurality of outcome vectors that represent all possible outcomes and the uncertainties associated with the decision problem, the decision model precluding any preference information of the attributes and the outcome vectors; determining whether the decision model can be solved without receiving any preference information from a decision maker; receiving partially specified preference information from the decision maker if the received decision model cannot be solved without any preference information, said receiving partially specified preference information comprising: identifying N pairs of outcome vectors to present to the decision maker for preference assessment, said N pairs of outcome vectors identified by: selecting the N pair of outcome vectors that maximizes an expected information gain, the expected information gain including: a reduction in a number of preferred strategies; or selecting the N pair of outcome vectors that balances user-friendliness and the expected information gain; presenting N elicitation questions, based on the identified N pairs of outcome vectors, to the decision maker, an elicitation question requesting of the decision maker which outcome vector the decision maker prefers between two outcome vectors; and providing, by the decision maker, answers to the N elicitation questions as representing the partially specified preference information; solving the decision model with the partially specified preference information; and recommending, based on the solution, one or more decisions to the decision maker, wherein a processor coupled to a memory device perform steps of: receiving the decision model, determining, receiving the partially specified preference information, solving, and recommending.