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This letter presents a minimum classification error learning formulation for a single-layer feedforward network (SLFN).
The performance of the proposed direct adaptive neural controller (DANC) is compared with feedback error learning neural controller (FENC).
We derive stability condition of the feedback error learning method based on the strict positiveness of the closed loop system.
This involved a bit of trial and error, learning which variables need to be set before waiting a little while and starting a conversion.
The weights updating was carried out according to the error, learning rate, and momentum terms (Delta rule).
Naïve crows either failed or solved the problem by trial and error learning.
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Reinforcement learning, by contrast, is more like the trial-and-error learning that young children use.
Leaders toss people willy-nilly into new situations, incurring the costs of trial-and-error learning instead of those associated with more carefully planned transitions.
Such fictitious learners can select actions with high payoffs without making long chains of trial-and-error learning.
Bootlegging emerges as an incremental continuous trial-and-error learning process in R&D and its uncertainty is no better or worse than that of 'normal' R&D.
"Perhaps the locals didn't consider themselves farmers because they were not farmers -- they were migrant workers in South African mines". Failure is, of course, part of trial-and-error learning.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com