Hello,
- You can use something like this. We do not have any examples with Reinforcement Learning Toolbox that show how to use this yet unfortunately.
- If it's challenging to estimate what a good episode reward is, you can run a singe training session for a good number of episodes (e.g. 5k episodes) to get some idea how the agent is doing and then use that knowledge from the training plot to set the 'SaveAgent' option as needed. Most of the time you will need to run multiple training sessions either way to tweak parameters, rewards, etc, so just use the first one to get some intuition.
