Management of communications between a remote or automated system and a supervisory human operator can be a formidable task. The selection of information for transmission is a recurrent, subjective decision involving many factors – machine state, operator capabilities, communications costs, and channel limitations, among others. An adaptive computer program has been developed which incorporates these various factors into a decision model resident in the remote element. The program is designed to capture the supervisory operator's decision policy by using a training algorithm based on pattern recognition techniques. Some exploratory studies of the technique are described.
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