LibtorchDRLControlTrainer
Overview
This object is supposed to train a Deep Reinforcement Learning (DRL) controller using the Proximal Policy Optimization (PPO) algorithm Schulman et al. (2017).
Example Input File Syntax
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The detailed documentation of this object is only available when Moose is compiled with Libtorch. For instructions on how to compile Moose with Libtorch, visit the general installation webpage or click here.
References
- John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov.
Proximal policy optimization algorithms.
arXiv preprint arXiv:1707.06347, 2017.[BibTeX]