Title of Paper: The Impact of Entropic Drag on Command and Control

A commonly believed axiom in signal detection theory is that "more information is good" (1). That is, when attempting to determine the state of a partially observable system the addition of correct information monotonically improves the correctness of the state assessment. When diagnosing static systems the assertion that "the effect of information is to increase the likelihood of getting correct diagnosis, while reducing the likelihood of incorrect diagnosis" holds. However, when diagnosing dynamic systems, the improvement in diagnosis is offset by increases in uncertainty generated by the dynamic forces within the system being observed. A similar effect occurs when controlling dynamic, stochastic systems. The act of exercising control requires a finite amount of time, during which uncertainty enters into the system reducing the efficacy of the control policy. The impact of information processing delays increases in relevance as the complexity and pace of both the system and control apparatus increase. This paper defines a mathematical framework describing the effect of information and information processing on the diagnosis of dynamic systems.