ABSTRACT
When agents cooperate to solve complex problems in the real world, they must choose which information to communicate from the mass of information that might affect the problem. A speaker should communicate the information that will be most helpful to the other agent. However, the speaker may not have a great deal of knowledge about the other. In addition, the speaker is also involved in reasoning about the collaborative problem solving task. So, processing that is done solely to select information will be taken from the resources available to work on the primary problem.
In this paper, we present preliminary work on a new approach to selecting information that should be included in a dialogue. Our approach uses the speaker’s knowledge of its own problem solving to determine how useful some piece of information might be to other agents. Consequently, the speaker can make its decision to include information in the dialogue using no additional knowledge and few additional computational resources beyond those required to reason about the primary problem solving task. We suggest heuristics which translate problem solving into estimates of how useful information will be for others.
