Strategically-controlled information fusion

Defines performance metrics that quantitatively characterize fusion engine (FE) output. Defines context metrics that quantitatively characterize FE performance as a function of input data. Quantitatively maps FEs´ performance space (how predicted performance depends on context). Encapsulates FEs so that they share data representations, services, and queries. Controls this confederation of encapsulated FEs with an intelligent fusion strategist that maximizes overall performance as a function of context by: (a) selecting the FE with the best-predicted performance for a given real-time context; (b) sequencing FEs to maximize performance by receiving data set outputs from other FEs, thus improving the region of the performance space in which they operate; (c) adjusting FE control and modeling parameters to achieve peak performance over a broader range of contexts; (d) reacting to FE outputs by comparing them to predicted performance and adjusting parameters, sequences, and selections to maintain overall performance