The current implementation of Proxima will not use an ML model if the ensemble of models produce 0 uncertainty for everything, which is the case when we start with a single pre-trained models (zero deviation between the predictions of the same model). That means that the model will never be used even if it is excellent.
Maybe we should assign a small positive value for the UQ even if there is a value of 0 so that it is possible for the model to run if the controller decides.
The current implementation of Proxima will not use an ML model if the ensemble of models produce 0 uncertainty for everything, which is the case when we start with a single pre-trained models (zero deviation between the predictions of the same model). That means that the model will never be used even if it is excellent.
Maybe we should assign a small positive value for the UQ even if there is a value of 0 so that it is possible for the model to run if the controller decides.