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Include SuperSuit in projects (#359)
* include supersuit * longer title underline * Update changelog.rst
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docs/misc/changelog.rst

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Documentation:
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^^^^^^^^^^^^^^
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- Added gym pybullet drones project (@JacopoPan)
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- Added link to SuperSuit in projects (@justinkterry)
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Release 1.0 (2021-03-15)

docs/misc/projects.rst

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@@ -61,3 +61,16 @@ PyBullet Gym environments for single and multi-agent reinforcement learning of q
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| Author: Jacopo Panerati
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| Github: https://github.com/utiasDSL/gym-pybullet-drones/
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| Paper: https://arxiv.org/abs/2103.02142
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SuperSuit
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---------
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SuperSuit contains easy to use wrappers for Gym (and multi-agent PettingZoo) environments to do all forms of common preprocessing (frame stacking, converting graphical observations to greyscale, max-and-skip for Atari, etc.). It also notably includes:
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-Wrappers that apply lambda functions to observations, actions, or rewards with a single line of code.
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-All wrappers can be used natively on vector environments, wrappers exist to Gym environments to vectorized environments and concatenate multiple vector environments together
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-A wrapper is included that allows for using regular single agent RL libraries (e.g. stable baselines) to learn simple multi-agent PettingZoo environments, explained in this tutorial:
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| Author: Justin Terry
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| GitHub: https://github.com/PettingZoo-Team/SuperSuit
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| Tutorial on multi-agent support in stable baselines: https://towardsdatascience.com/multi-agent-deep-reinforcement-learning-in-15-lines-of-code-using-pettingzoo-e0b963c0820b

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