naokiuchida

naokiuchida's Stars

• reinforcement-learning-kr/pg_travel

  Policy Gradient algorithms (REINFORCE, NPG, TRPO, PPO)

  Language:Python36776

• sfujim/TD3

  Author's PyTorch implementation of TD3 for OpenAI gym tasks

  Language:Python1.7k434

• l5shi/Multi-DDPG-with-parameter-noise

  New reinforcement algorithm base on DDPG

  Language:Jupyter Notebook173

• mynameisfiber/high_performance_python

  Code for the book "High Performance Python" by Micha Gorelick and Ian Ozsvald with OReilly

  Language:Python733282

• jnishii/python-rl-introduction

  Language:Jupyter Notebook33

• fastai/fastai

  The fastai deep learning library

  Language:Jupyter Notebook26.2k7.5k

• matsuolab-edu/dl4us

  Language:Jupyter Notebook1.2k247

• CMA-ES/pycma

  Python implementation of CMA-ES

  Language:Jupyter Notebook1.1k177

• NotAnyMike/gym

  An improvement of CarRacing-v0 from OpenAI Gym in order to make the environment complex enough for Hierarchical Reinforcement Learning

  Language:Python7024

• gui-miotto/DeepLearningLab

  Language:Jupyter Notebook2110

• ray-project/ray

  Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

  Language:Python33.3k5.6k

• icoxfog417/baby-steps-of-rl-ja

  Pythonで学ぶ強化学習 -入門から実践まで- サンプルコード

  Language:Jupyter Notebook430261

• xl-sr/CAL

  [CoRL'18] Conditional Affordance Learning

  Language:Python6927

• avisingh599/reward-learning-rl

  [RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering

  Language:Python36768

• tejus-gupta/hybrid-astar-planner

  Hybrid A* Path Planner

  Language:C++335102

• karlkurzer/path_planner

  Hybrid A* Path Planner for the KTH Research Concept Vehicle

  Language:C++1.6k538

• MLCS-Yonsei/Factory_RL_Gazebo

  Youbot simulator (SLAM & Navi)

  Language:Python51