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Udacity Reacher Project with Unity (#79)
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* Add the reacher project to the sample projects

* Update the change log

* Remove github incompatible link notation

* Update changelog.rst

Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
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koulakis and araffin committed Jun 30, 2020
1 parent 08e7519 commit 7d8ebb9
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3 changes: 2 additions & 1 deletion docs/misc/changelog.rst
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Expand Up @@ -37,6 +37,7 @@ Documentation:
^^^^^^^^^^^^^^
- Updated notebook links
- Fixed a typo in the section of Enjoy a Trained Agent, in RL Baselines3 Zoo README. (@blurLake)
- Added Unity reacher to the projects page (@koulakis)



Expand Down Expand Up @@ -339,4 +340,4 @@ And all the contributors:
@Miffyli @dwiel @miguelrass @qxcv @jaberkow @eavelardev @ruifeng96150 @pedrohbtp @srivatsankrishnan @evilsocket
@MarvineGothic @jdossgollin @SyllogismRXS @rusu24edward @jbulow @Antymon @seheevic @justinkterry @edbeeching
@flodorner @KuKuXia @NeoExtended @PartiallyTyped @mmcenta @richardwu @kinalmehta @rolandgvc @tkelestemur @mloo3
@tirafesi @blurLake
@tirafesi @blurLake @koulakis
12 changes: 12 additions & 0 deletions docs/misc/projects.rst
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Expand Up @@ -25,3 +25,15 @@ It was the starting point of Stable-Baselines3.
| Author: Antonin Raffin, Freek Stulp
| Github: https://github.com/DLR-RM/stable-baselines3/tree/sde
| Paper: https://arxiv.org/abs/2005.05719
Reacher
-------
A solution to the second project of the Udacity deep reinforcement learning course.
It is an example of:

- wrapping single and multi-agent Unity environments to make them usable in Stable-Baselines3
- creating experimentation scripts which train and run A2C, PPO, TD3 and SAC models (a better choice for this one is https://github.com/DLR-RM/rl-baselines3-zoo)
- generating several pre-trained models which solve the reacher environment

| Author: Marios Koulakis
| Github: https://github.com/koulakis/reacher-deep-reinforcement-learning

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