HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
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feature: combine worker argument both from trainer and worker #330
Essentially, variables that can be decided by the worker want to be decided by the worker.
Furthermore, if there is a default value on the trainer's side, we would like to use it.
Essentially, variables that can be decided by the worker want to be decided by the worker. Furthermore, if there is a default value on the trainer's side, we would like to use it.