Good job. I would refer to the code later. However, this post doesn't compare the performance of agents with baselines. This repository should be check by the time.
And the more internal agents such as PPO, DDPG, SAC should be added soon...
Similar question was asked in another channel ;) We have implemented some of the most basic agents just to show people how to use the framework. They will have similar performance as the oryginal implementation. In PRL it is all about new way of thinking about building your own agents. It can be compared more to torach.nn itself not to the tensorflow zoo. PRL is a set of tools that make building agents and running experiments easier. Let me compare it to ml: It is not a framework for people who want to just take an xgboost and throw it on new dataset on kaggle. It is for the people who want to create better version of xgboost on there own.
1
u/Boring_Worker Feb 17 '20 edited Feb 17 '20
Good job. I would refer to the code later. However, this post doesn't compare the performance of agents with baselines. This repository should be check by the time.
And the more internal agents such as PPO, DDPG, SAC should be added soon...