Adding a2c_sb3_cartpole.py using stable_baselines3

a2c_sb3_cartpole.py

+import gym
+from stable_baselines3 import A2C
+from stable_baselines3.common.vec_env import DummyVecEnv
+
+# Create the CartPole environment
+env = gym.make('CartPole-v1')
+
+# Wrap the environment in a DummyVecEnv to handle multiple environments
+env = DummyVecEnv([lambda: env])
+
+# Initialize the A2C model
+model = A2C('MlpPolicy', env, verbose=1)
+
+# Train the model for 1000 steps
+model.learn(total_timesteps=1000)
+
+#Saving the model
+model.save("a2c_sb3_cartpole")
+
+# Test the trained model
+obs = env.reset()
+for i in range(1000):
+    action, _states = model.predict(obs)
+    obs, rewards, dones, info = env.step(action)
+    env.render()
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