Copy over experiments

scratch/etienne/intersimple/ppo_intersimple_tspeed.py

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+from stable_baselines3 import PPO
+from stable_baselines3.common.env_util import make_vec_env
+from intersim.envs.intersimple import IntersimpleTargetSpeed
+
+env = IntersimpleTargetSpeed()
+
+model = PPO("MlpPolicy", env, verbose=1)
+model.learn(total_timesteps=25000)
+model.save("ppo_intersimple")
+
+print('Done training.')
+
+del model # remove to demonstrate saving and loading
+
+model = PPO.load("ppo_intersimple")
+
+obs = env.reset()
+while True:
+    action, _states = model.predict(obs)
+    obs, rewards, done, info = env.step(action)
+    env.render(mode='post')
+    if done:
+        break
+
+env.close()