Skip to Main Content
When tasks are allocated dynamically within a human-computer system, system performance depends upon effective communication between the human and the computer. The results are presented of simulation studies which investigate two means of human-to-computer communication: implicit communication, in which the human's planned actions are conveyed to the computer through a model of the human's action strategy; and explicit communication, in which the human overtly transmits decisions to the computer. The results indicate that the effectiveness of implicit communication depends upon both the predictive validity of the model employed and the computer task allocation strategy built upon the model. The effectiveness of explicit communication depends upon the time the human must devote to transmitting action plans to the computer. These simulations indicate the payoffs that can be realized by optimization of implicit and explicit human-computer communication. They also provide an efficient means to determine the appropriate mix of these communication techniques for a given situation. Perhaps the most interesting finding is that implicit communication based upon a model possessing only modest predictive validity is capable of enhancing system performance. This suggests that implementation of implicit communication within human-computer systems need not require the development and use of complex all-encompassing models of human performance.