Secondly, a tight relationship is guaranteed between computation invested and closeness to the reference behavior.
Our approach designs a reference behavior with a classical consensus method.
This technique aims at designing a non-linear controller that constrains the system outputs to follow a linear reference behavior.
The main novelty is using optimistic optimization (OO) to find controls that closely follow the reference behavior.
The outcomes are compared with the reference behavior of the undamped system which allows for semi-analytical solution.
Modeling the effect of memory size on page faults is very difficult, because they are the result of the interaction between process reference behavior and page replacement policy.
To reflect this second interpretation, let us define the relative robustness of a system with respect to a nominal behavior as the system's robustness divided by its nominal performance, that is, by the satisfaction degree of the reference behavior.
The Δn parameter therefore appears as a corrective value related to TIS/e, figuring out the offset existing between the sample behavior and a first-order scattering reference behavior, quantifying the effects due to multi-scattering in particular.
Intuitively, the violation degree reflects the distance between a particular behavior of the perturbed system, given as a numerical timed trace, and the expected reference behavior, expressed by a temporal logic formula.
A knowledge flow (KF) represents an individual's or group's knowledge-needs and referencing behavior of codified knowledge during the performance of organizational tasks.
