Consensus Theory in Expert Systems: An Adaptive Inference Framework and Application to Image Understanding

摘要

Advances in automated image understanding technology are essential to our ability to exploit today's sophisticated imagery capabilities to support battlefield intelligence requirements. This report describes the application of a unique inference framework, Non-Monotonic Probabilist, to the problem of achieving consensus among modules, each of which supports a different part of the image understanding problem.