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Additional tests are needed to ensure the correct behaviour of each optimization algorithm and its parameters (like epsilon in hill-climbing).
This is difficult to test, because it requires a specialized optimization setup that is different for each parameter. An example for this could be to set epsilon of hill-climbing to 1/inf and validate, that all positions in the search-data are the same. So this requires a lot of work to complete for all algorithms and parameters.
Additional tests are needed to ensure the correct behaviour of each optimization algorithm and its parameters (like epsilon in hill-climbing).
This is difficult to test, because it requires a specialized optimization setup that is different for each parameter. An example for this could be to set
epsilon
of hill-climbing to 1/inf and validate, that all positions in the search-data are the same. So this requires a lot of work to complete for all algorithms and parameters.An example test for hill-climbing can be seen here:
https://github.com/SimonBlanke/Gradient-Free-Optimizers/blob/version/1.4/tests/test_parameters/test_hill_climbing.py
Suggestions on how to test parameters are welcome :-)
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