Trustworthy Situation Assessment via Belief Networks
S. Das and D. Lawless
Proceedings of the 5th International Conference on Information Fusion, Annapolis, Maryland, Invited Session on Information Fusion Using Bayesian Networks, (July, 2002)
We present a Network-based Truth Maintenance System (NTMS) for problem solvers based on Bayesian belief network (BN) technology. BN technology has been proven to be effective in various domains, e.g. assessing battlefield situations, such as the enemy’s likely point of interdiction. Nodes and links in a BN capture semantic relationships among various domain related concepts. In the absence of firmer knowledge, default assumptions provide the beliefs of some nodes in a BN. Before posting incoming evidence into a BN node, a truth maintenance procedure is invoked to check for information consistency between the node’s current expected state and the new observed state. In case of inconsistency, the truth maintenance procedure revises some default assumptions, by isolating those nodes causing inconsistency, via a sensitivity analysis procedure that exploits the strengths of BN causal dependency. We have applied our approach for trustworthy situation assessment in the context of a military Stability and Support Operation (SASO) scenario.
Consistency checking belief network for military sensor array
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