In this paper, two schemes are proposed to facilitate the process of information acquisition for the decision maker in a discrete resource allocation problem (RAP). The RAP, often encountered in artificial intelligence (AI), economics, and operations research, requires the decision maker to recognize the utility functions of agents before the final allocation of resources is made. The acquisition of information on agents' utility functions is achieved by the decision maker through a sequential process that asks the agents about their preference profiles. These two schemes are demonstrated to be effective and compared to show one scheme is theoretically and practically better than the other