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The base class for point representation is RepBase.
For example, the Point representation objects use it for drawing.
This is what is called a point representation in this tool kit.
It also delegates its task of draw the Projected Value object to a Point representation.
The name float comes from the way in which real numbers are represented in Python: a "floating point" representation.
Also the comparison between binary versus floating point representation of the design variables show some superiority of the latter.
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This framework consists of two components: reinforcement learning and via-point representation.
scale-float returns (* float (expt (float b float) integer)), where b is the radix of the floating-point representation.
Inherently, compared with the floating-point representation, the fixed-point representation would make the search space miss much useful gradient information and therefore, surely rises new challenges for continuous EAs.
The higher level is implemented using via-point representation, which corresponds to macro-actions or multiple time scales.
The speedup is due to three major factors: fixed-point representation, custom memory interface design, and pipelining and parallelism.
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