LibtorchDRLControlTrainer

Overview

This object trains an on-policy actor-critic controller using Proximal Policy Optimization (PPO) Schulman et al. (2017) together with generalized advantage estimation (GAE) Schulman et al. (2015). Reporter trajectories are assembled into transitions, flattened across samples, shuffled into mini-batches, and then used to update separate actor and critic neural networks.

warning

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, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel. High-dimensional continuous control using generalized advantage estimation. arXiv preprint arXiv:1506.02438, 2015.

BibTeX

@article{schulman2015gae,
    author = "Schulman, John and Moritz, Philipp and Levine, Sergey and Jordan, Michael and Abbeel, Pieter",
    title = "High-dimensional continuous control using generalized advantage estimation",
    journal = "arXiv preprint arXiv:1506.02438",
    year = "2015"
}

RIS

TY  - JOUR
AU  - Schulman, John
AU  - Moritz, Philipp
AU  - Levine, Sergey
AU  - Jordan, Michael
AU  - Abbeel, Pieter
TI  - High-dimensional continuous control using generalized advantage estimation
JO  - arXiv preprint arXiv:1506.02438
PY  - 2015
ER  -

Plain Text

John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel. High-dimensional continuous control using generalized advantage estimation. arXiv preprint arXiv:1506.02438, 2015.

John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347, 2017.

BibTeX

@article{schulman2017proximal,
    author = "Schulman, John and Wolski, Filip and Dhariwal, Prafulla and Radford, Alec and Klimov, Oleg",
    title = "Proximal policy optimization algorithms",
    journal = "arXiv preprint arXiv:1707.06347",
    year = "2017"
}

RIS

TY  - JOUR
AU  - Schulman, John
AU  - Wolski, Filip
AU  - Dhariwal, Prafulla
AU  - Radford, Alec
AU  - Klimov, Oleg
TI  - Proximal policy optimization algorithms
JO  - arXiv preprint arXiv:1707.06347
PY  - 2017
ER  -

Plain Text

John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347, 2017.

Overview
References

Theory

Usage

Development

LibtorchDRLControlTrainer

Overview

References