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TIGER:: AN UNSUPERVISED MACHINE LEARNING TACTICAL INFERENCE GENERATOR

TIGER:: AN UNSUPERVISED MACHINE LEARNING TACTICAL INFERENCE GENERATOR

Автор: D. Ezra Sidran, 160 стр., ISBN: 3838352815

TIGER is a Tactical Inference Generator computer program designed to test the following hypotheses: Hypothesis 1: There is agreement among military experts that tactical situations exhibit certain features and that these features can be used to group tactical situations by similarity. Hypothesis 2: The best match by TIGER of a new scenario to a scenario from its historical database predicts what the experts would choose. We have conducted three surveys of SMEs and have concluded that there is a statistically significant confirmation of Hypothesis 1. The statistical confidence level for this confirmation of Hypothesis 1 is greater than twice the prior probability. In order to test Hypothesis 2 we constructed a series of algorithms for the analysis of SME identified tactical features including: interior lines, restricted avenues of approach, restricted avenues of attack, slope of attack, weighted force relationships and anchored or unanchored flanks. Lastly, we present TIGER?s...
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