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if we replace arms_w_rew = (r > 0.) with arms_w_rew = (r != 0.) then "BootstrappedUCB" and "BootstrappedTS" could work and incorporate negative rewards (I guess).
The text was updated successfully, but these errors were encountered:
Plus other methodological aspects which specifically exploit the assumption of rewards being binary, like the usage of a beta distribution whose priors are updated iteratively, or the calculation of uncertainty in active learning criteria.
Hence, you might find that changing that line might be sufficient for allowing negative rewards for some particular combinations of input parameters, but it will not guarantee that everything else will work along with them.
In the following line
https://github.com/david-cortes/contextualbandits/blob/7b87efe31ffefdbc95a125d557920ab5b13105c5/contextualbandits/utils.py#L912C13-L912C34
if we replace arms_w_rew = (r > 0.) with arms_w_rew = (r != 0.) then "BootstrappedUCB" and "BootstrappedTS" could work and incorporate negative rewards (I guess).
The text was updated successfully, but these errors were encountered: