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resibots/blackdrops

0
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66 stars·22 forks·C++·7 views

Blackdrops

Code for the Black-DROPS algorithm: "Black-Box Data-efficient Policy Search for Robotics", IROS 2017/ICRA 2018

Features

  • Algorithm Implementations - Modular code for model-based policy search algorithms.
  • Reinforcement Learning Frameworks - Modular code for model-based policy search and simulator integration.

Star history

Star history chart for resibots/blackdropsStar history chart for resibots/blackdrops

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does resibots/blackdrops do?

Code for the Black-DROPS algorithm: "Black-Box Data-efficient Policy Search for Robotics", IROS 2017/ICRA 2018

What are the main features of resibots/blackdrops?

The main features of resibots/blackdrops are: Algorithm Implementations, Reinforcement Learning Frameworks.

What are some open-source alternatives to resibots/blackdrops?

Open-source alternatives to resibots/blackdrops include: nivwusquorum/tensorflow-deepq — A deep Q learning demonstration using Google Tensorflow. openai/baselines — Baselines is a comprehensive suite of frameworks for reinforcement learning algorithm implementation, imitation… chainer/chainerrl — ChainerRL is a deep reinforcement learning library built on top of Chainer. instadeepai/jumanji — 🕹️ A diverse suite of scalable reinforcement learning environments in JAX. kaixhin/atari — Persistent advantage learning dueling double DQN for the Arcade Learning Environment. rlcode/reinforcement-learning — Minimal and Clean Reinforcement Learning Examples.