What should learners do when fed the same point twice about adaptive

[basnijholt]

originally posted by Jorn Hoofwijk (@Jorn) at 2018-09-17T18:26:22.524Z on GitLab

I think it is indeed best practice to just raise an exception, as we should not allow this to happen.

If for some reason I cannot think of, we would need to silently ignore it we could set some variable strict mode (which defaults to True) in the init call, and then if we encounter a double point we will throw an error, unless strict mode is set to False, then we silently ignore

so you would then create a learner by:

learner = LearnerND(func, bounds=[(-1,1),(-1,1)]) # for normal behaviour)
learner = LearnerND(func, bounds=[(-1,1),(-1,1)], strict=False) # for allowing a user to add the same point twice, for whatever reason they would want this

[basnijholt]

originally posted by Anton Akhmerov (@anton-akhmerov) at 2018-09-24T19:22:39.053Z on GitLab

ignore or overwrite?

[basnijholt]

originally posted by Bas Nijholt (@basnijholt) at 2018-12-07T19:44:56.320Z on GitLab

We have decided that we should do the following:

def tell(self, x, y):
    if x in self.data:
        # The point is already evaluated before
        return
    
    # Add point to the data dict
    self.data[x] = y

    # remove from set of pending points
    self.pending_points.discard(x)

    if not self.bounds[0] <= x <= self.bounds[1]:
        # if outside of the domain, stop.
        return

    update_the_other_data_structure_such_as_loss(...)

This is implemented in all the learners ATM.