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Update units/en/unitbonus3/envs-to-try.mdx

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Co-authored-by: Thomas Simonini <simonini.thomas.pro@gmail.com>
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Alessandro Palmas
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@@ -21,7 +21,7 @@ They all support both single player (1P) as well as two players (2P) mode, makin
[Interfaced games](https://docs.diambra.ai/envs/games/) have been selected among the most popular fighting retro-games. While sharing the same fundamental mechanics, they provide different challenges, with specific features such as different type and number of characters, how to perform combos, health bars recharging, etc.
DIAMBRA Arena is built to maximize compatibility will all major Reinforcement Learning libraries. It natively provides interfaces with the two most important packages: Stable Baselines 3 and Ray RLlib, while Stable Baselines is also available but deprecated. Their usage is illustrated in the [official documentation](https://docs.diambra.ai/) and in the [DIAMBRA Agents examples repository](https://github.com/diambra/agents). It can easily be interfaced with any other package in a similar way.
DIAMBRA Arena is built to maximize compatibility will all major Reinforcement Learning libraries. It natively provides interfaces with the two most important packages: [Stable Baselines 3](https://stable-baselines3.readthedocs.io/en/master/) and [Ray RLlib](https://docs.ray.io/en/latest/rllib/index.html), while Stable Baselines is also available but deprecated. Their usage is illustrated in the [official documentation](https://docs.diambra.ai/) and in the [DIAMBRA Agents examples repository](https://github.com/diambra/agents). It can easily be interfaced with any other package in a similar way.
### Competition Platform