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Deep RL with Gymnasium

Install Gymnasium

!pip install gymnasium 

Import the prerequisite packages

import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
import torch.distributions as distributions
import numpy as np
import gymnasium as gym  

Check the available environments

import gymnasium as gym
for i in gym.envs.registry.keys():
    print(i)

Create a new CartPole-v1 environment

import gymnasium as gym
env = gym.make('CartPole-v1')

Check the observation space

print("observation space: ", env.observation_space)

Check an example of an observation

observation, info = env.reset()
print("observation: ", observation)

Check the action space

print("action space: ", env.action_space)
env = gym.make('CartPole-v1')