Displaying 1 to 7 from 7 results

tensorlayer - Deep Learning and Reinforcement Learning Library for Developers and Scientists

  •    Python

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides a large collection of customizable neural layers / functions that are key to build real-world AI applications. TensorLayer is awarded the 2017 Best Open Source Software by the ACM Multimedia Society. Simplicity : TensorLayer lifts the low-level dataflow interface of TensorFlow to high-level layers / models. It is very easy to learn through the rich example codes contributed by a wide community.




pytorch-a3c-mujoco - Implement A3C for Mujoco gym envs

  •    Python

Note that this repo is only compatible with Mujoco in OpenAI gym. If you want to train agent in Atari domain, please refer to pytorch-a3c. There're three tasks/modes for you: train, eval, develop.

pytorch-A3C - Simple A3C implementation with pytorch + multiprocessing

  •    Python

This is a toy example of using multiprocessing in Python to asynchronously train a neural network to play discrete action CartPole and continuous action Pendulum games. The asynchronous algorithm I used is called Asynchronous Advantage Actor-Critic or A3C. I believe it would be the simplest toy implementation you can find at the moment (2018-01).

tf-a3c-gpu - Tensorflow implementation of A3C algorithm

  •    Python

Tensorflow implementation of A3C algorithm using GPU (haven't tested, but it would be also trainable with CPU). On the original paper, "Asynchronous Methods for Deep Reinforcement Learning", suggests CPU only implementations, since environment can only be executed on CPU which causes unevitable communication overhead between CPU and GPU otherwise.