Figure 1 gives pseudo-code outlining how active learning is implemented.
Given this background, we then describe the basic extraction algorithm in pseudo code.
We always assume that is convex, so that the structure is pseudo- - - convex.
Basically, a pseudo-object is created for every combination of possible case.
The pseudo code for our current composition algorithm is given below.
The target moved pseudo-randomly during two segments of each trial, whereas the other segment was the same throughout the four sessions.
Moreover, several of his incorrect responses for novel verbs had -ed endings that contained a pause before the -ed ending, consistent with a pseudo-suffixation strategy.
Clearly, these semicircles form a collection of pseudo-segments, that is, each pair of them intersects at most once.
