Online Situation Awareness and Knowledge Aquisition

Gonsalves, P., Burge, J., and Call C.

SPIE Defense and Security Symposium, vol 5809, Orlando, FL (March)

In dynamic environments, effective decision-making is highly dependent on situation awareness (SA). Belief networks (BNs) are an ideal tool for modeling and meeting the requirements of tactical situation awareness. BNs emulate a skilled person’s information fusion and reasoning process in a multi-task environment in the presence of uncertainty. While belief networks offer significant advantages for SA, a key drawback to their use in the daunting issue of how the requisite knowledge is captured or elicited to both build the network and populate the Condition Probability Tables (CPTs). To address this issue, we have built the Situation Awareness and Knowledge Acquisition (OSAKA) system. This system consists of two parts: development of a libary of BN components that can be combined to describe different air operation situations and enhancing our BNet.Builder™ toolkit to learn CPT values for these components based on data obtained from running an external application. This allows the initial CPT values obtained from our Subject Matter Expert to be tuned based on what actually happens. The ability to tune the network over time can aid in supplying information not initially available when constructing the network and to help ensure that it continues to provide current, useful information

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