[Proposal] Tutorials

To encourage the use of Gymnasium and build up the RL community, I would propose that a large range of tutorials are created.

This is a list of tutorials that could be made

Implementation of a custom environment
DQN for atari implementation (doesn’t need to be fast)
Training an agent for the new Phys3d / Phys2d environments (brax) using pytorch or jax
Frozenlake training results with different map sizes
Gym vectorisation (gym.vector.make)
Training agents for the blackjack environment, it has Tuple observation space
How to use the action sample masking, with example from Taxi
Car racing, comparing agents with continuous and discrete action spaces
Training a deep RL agent with pytorch (with the new step API)
Using gym make, spec, register and registry
Understand the gym spaces
Exploring the impact of bipedal walker hardcore parameter on agent performance
Train an agent with stable-baselines-3
Train an agent with tianshou
Using gym for Multi-agent RL
Using gym for Offline RL with D4RL
How to render an environment
How to develop an environment using the gym MDP API
Using the gym wrappers and developing custom wrappers
visualising your agent with gym.utils.play
Understanding the gym environment checker
Experimenting with classic control reset options random state bounds
Add environment or example using the Graph space
Add example with entity neural network using the Sequence space