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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')