pytorch-trpo
Optimization algorithm
A PyTorch implementation of an optimization algorithm for continuous control and reinforcement learning tasks
PyTorch implementation of Trust Region Policy Optimization
435 stars
12 watching
91 forks
Language: Python
last commit: over 6 years ago continuous-controldeep-learningdeep-reinforcement-learningmujocopytorchreinforcement-learningtrpotrust-region-policy-optimization
Related projects:
Repository | Description | Stars |
---|---|---|
| A PyTorch implementation of meta-learning using gradient descent to adapt to new tasks. | 312 |
| An implementation of reinforcement learning algorithms for continuous control tasks using deep neural networks. | 307 |
| An implementation of an optimization algorithm inspired by a 2016 research paper | 33 |
| A PyTorch implementation of Distributed Proximal Policy Optimization algorithm | 180 |
| PyTorch implementations of algorithms for density estimation using invertible transformations. | 577 |
| An optimizer that automatically tunes momentum and learning rate using local quadratic approximation. | 287 |
| An implementation of an A3C algorithm for reinforcement learning in Pytorch, with various optimizations and extensions to accelerate training. | 562 |
| An implementation of Neural Combinatorial Optimization with Reinforcement Learning using PyTorch. | 562 |
| A lightweight wrapper around PyTorch to prevent CUDA out-of-memory errors and optimize model execution | 1,823 |
| A PyTorch toolbox for supporting research and development of domain adaptation, generalization, and semi-supervised learning methods in computer vision. | 1,236 |
| A PyTorch module that adds differentiable optimization as a layer to neural networks | 517 |
| Replication of Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks in PyTorch for reinforcement learning tasks | 830 |
| An efficient library for differentiable optimization built on top of PyTorch. | 554 |
| A PyTorch implementation of the REINFORCE algorithm for reinforcement learning in continuous and discrete environments. | 266 |
| A PyTorch module that wraps the OSQP solver for differentiable optimization problems | 59 |