Simon Blanke
Simon Blanke
The number of initial positions should be automatically increased if n_population increases. It will reduce the steps the user needs to take to change this parameter.
[As discussed in this PR](https://github.com/SimonBlanke/Hyperactive/pull/58): It would be interesting to see how the newest versions of python (v3.11) speed up different optimization tasks.
This adds a way to change the parameters of the optimization algorithms during runtime (e.g. `epsilon` from the hill-climbing optimizer). My idea is to enable this within the objective function....
There appears to be a bug in the initial sampler of the sequence-model-based optimization algorithms that only occurs in the "test_large_search_space.py"-tests. This is the error: ```python gradient_free_optimizers/search.py:96: in search self.search_step(nth_trial)...
As a reference there is [Ant Colony Optimization by Marco Dorigo and Thomas Stützle](https://web2.qatar.cmu.edu/~gdicaro/15382/additional/aco-book.pdf).
In this issue I will show the progress of adding support for continuous parameter ranges in the search-space. For most optimization algorithms it should be easy to add support for...