Abstract

A new approach to situation assessment is an automated distributed sensor network (DSN) consisting of many "intelligent" sensor devices that can pool their knowledge to achieve an accurate overall assessment of a situation. Laboratory experiments were conducted to investigate potential DSN organizations and to ascertain some general design principles. These experiments have been performed with a network of "sensor nodes," each of whom sees only a small portion of the entire environment and attempts to identify the environmental mobile entities as quickly as possible. To do this, they must cooperatively communicate their hypotheses and data, using a limited number of messages. Two general DSN organizations were tested. The first was hierarchical. The second was an "anarchic committee" whose nodes could each send messages to one, some, or all other nodes. The performance of the committee organization consistently surpassed the hierarchical one. This lent support to the contention that DSN architectures need to emphasize cooperative aspects of problem-solving. A machine-based simulation of such a network that achieved performance levels comparable to that of the human committee DSN organization was also constructed and tested. Because most situation assessment communications concern hypothesis updating and revision, minimizing communication requirements through the concept of active "hypothesis processes," which are responsible for predicting their own evolution over time, is suggested.

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