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The models of the logic can have probabilistic aspects, the notion of consequence can have a probabilistic flavor, or the language of the logic can contain probabilistic operators.
As was explained in Section 1 of this entry, there are many ways in which a logic can have probabilistic features.
So again, the methods do not presuppose that the variable sets for which we have probabilistic information themselves satisfy the MC.
Therefore, via these mappings and the results presented in the previous section, we have probabilistic models for the generalized Horn fragments of the logics V of Lewis, NP of Delgrande and B of Burgess.
If our choices are events which have probabilistic causes (e.g., our beliefs, desires, and other reasons for acting), then it no longer seems plausible to say that we have no control over them.
Additionally, in cr(mathcal{ALC }) one can have probabilistic inclusions such as (P(C|D)= alpha ) or (P r)=beta ) for concepts (C) and (D), and for role (r) (in this paper we only consider equality in probabilistic inclusions/definitions).
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The topology optimization problem is reformulated as a volume minimization problem having probabilistic displacement constraints using the performance measure approach.
Since natural precipitation is a random process and has probabilistic characteristics, it will be more appropriate to describe these probabilistic features of rainfall and its relationship with design storage capacity as well as supply deficit of RHS.
Such Pareto front is then obtained for single inverted pendulum having probabilistic uncertainties in its parameters using the statistical moments of those objective functions through a Monte Carlo simulation (MCS) approach.
In the latter case, the decision maker has probabilistic information about the possible states of the world.
The aim was to keep average number of active hosts as minimum while having probabilistic SLA guaranty for VMs.
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