ztz695183179

Attention-based-Bidirectional-LSTM-Network

Benchmark-Efficient-Reinforcement-Learning-with-Demonstrations

Benchmark present methods for efficient reinforcement learning. Methods include Reptile, MAML, Residual Policy, etc. RL algorithms include DDPG, PPO.

biLSTM_attn

Deep-Reinforcement-Learning-for-Continuous-Control-Docking-of-Autonomous-Underwater-Vehicles

Code for the thesis

gym-ignition

Framework for developing OpenAI Gym robotics environments simulated with Ignition Gazebo

gym_dockauv

Gym Environment for AUV docking procedure

openai

PyAdvancedControl

Python codes for advanced control

reinforcement_learning

[动手学强化学习]系列，基于pytorch。

ztz695183179/Benchmark-Efficient-Reinforcement-Learning-with-Demonstrations

Benchmark present methods for efficient reinforcement learning. Methods include Reptile, MAML, Residual Policy, etc. RL algorithms include DDPG, PPO.

ztz695183179/biLSTM_attn

ztz695183179/Deep-Reinforcement-Learning-for-Continuous-Control-Docking-of-Autonomous-Underwater-Vehicles

Code for the thesis

ztz695183179/gym-ignition

Framework for developing OpenAI Gym robotics environments simulated with Ignition Gazebo

ztz695183179/Attention-based-Bidirectional-LSTM-Network

ztz695183179/gym_dockauv

Gym Environment for AUV docking procedure

ztz695183179/openai

ztz695183179/PyAdvancedControl

Python codes for advanced control

ztz695183179/reinforcement_learning

[动手学强化学习]系列，基于pytorch。