Mohammad Momayezi

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Same problem here! Solution mentioned by @AlexLiddiard solved the issue. But why it hasn't been fixed yet on elegantrl?!

I traced the issue but not sure how to solve it yet. In the `train_and_evaluate` function in `run.py`, `agent.explore_env()` returns a list of 5 tensors while it's supposed to return...

In addition to changing `agent` to `agent_class` in elegantrl_models.py, the run.py in elegantrl had to be modified as well.

How do you set your environment?

I understand. But I'm running the exact the same code with a constant random seed. The results does not change no matter how many times I run the code whether...