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Decision functions and decision boundaries.
An accurate approximated explicit decision functions is obtained with a reduced number of function evaluations.
This article presents a methodology to generate explicit decision functions using support vector machines (SVM).
Support vector machines (SV machines, SVMs) often contain many SVs, which reduce runtime speeds of decision functions.
To simplify the decision functions and improve SVM succinctness, the efforts to remove SVs in trained SVMs have been made.
Three problems are presented to demonstrate the efficiency of the update scheme to explicitly reconstruct known analytical decision functions.
We investigate the properties of a negotiation mechanism that is based on negotiation decision functions (NDFs) in an agent-based system.
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In this work a continuous decision function is anticipated.
especially when at least one time-varying operating decision function needs to be selected.
For this reason, an adaptive sampling scheme that updates the decision function is proposed.
It is a group decision function and cannot be done on an individual basis.
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