Authors:
Vaughn H. Standley
;
Frank G. Nuño
and
Jacob W. Sharpe
Affiliation:
College of Information and Cyberspace, National Defense University, 300 5th Ave., Washington D.C. and U.S.A.
Keyword(s):
Complex Systems, Bayesian Minimization, Deterrence, Likelihood Ratio, Power-law, Log-normal, Log-gamma.
Abstract:
Strategic deterrence operates in and on a vast interstate network of rational actors seeking to minimize risk. Risk can be minimized by employing a likelihood ratio test (LRT) derived from Bayes’ Theorem. The LRT is comprised of prior, detection, and false-alarm probabilities. The power-law, known for its applicability to complex systems, has been used to model the distribution of combat fatalities. However, it cannot be used as a Bayesian prior for war when its area is unbounded. Analytics applied to Correlates of War data reveals that combat fatalities follow a log-gamma or log-normal probability distribution depending on a state’s escalation strategy. Results are used to show that nuclear war level fatalities pose increasing risk despite decreasing probability, that LRT-based decisions can minimize attack risk if an upper limit of impending fatalities is indicated by the detection system and commensurate with nominal false-alarm maximum, and that only successful defensive strategi
es are stable.
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