Brenden Petersen

A third way would be to use the `poly` token. This will be optimized analytically, meaning it is very fast and doesn't require an inner optimization loop. The function `[gaussian,...

> Reward over all values should then go to the generator, so we have the target to increase the reward numbers... I currently see with my results the reward is...

A PyTorch re-implementation of DSO is coming... our team is full-time researchers, not software developers, so while we know this is important for people it's hard to be our priority....

I’d recommend forking off this repo instead of re-implementing your own from scratch! There are lots of new tasks and features on the horizon, so a re-implementation will not be...

If your control task uses PyTorch, that’s totally fine as the task is separate from the compute graph of the DSO policy. So it could mix TF and PyTorch. But...

Probably just PyTorch. It shouldn’t be that hard to support both TF2 and PyTorch at once now that our latest release separates the `Policy` object from the `PolicyOptimizer` (algorithms and...

But there's lots of other cool stuff coming! For example, we will release support for multi-objective optimization (currently DSO only supports scalar objectives). Or possibly `Policy`s that support hybrid discrete-continuous...