initial data commit.

sac_main.py

@@ -0,0 +1,52 @@
+import gymnasium as gym
+import numpy as np
+from stable_baselines3 import SAC
+from stable_baselines3.common.env_util import make_vec_env
+from stable_baselines3.common.monitor import Monitor
+from stable_baselines3.common.vec_env import VecMonitor
+
+from car_racing_env import CarRacing
+
+SEED = 5
+
+
+def make_env():
+    env = CarRacing(render_mode=None)
+    env.reset(seed=SEED)
+    return Monitor(env)
+
+
+venv = make_vec_env(make_env, n_envs=1)
+venv = VecMonitor(venv)
+
+model = SAC(
+    "MlpPolicy",
+    venv,
+    seed=SEED,
+    learning_rate=3e-4,
+    buffer_size=300_000,
+    batch_size=256,
+    tau=0.01,
+    gamma=0.99,
+    train_freq=(1, "step"),
+    gradient_steps=1,
+    ent_coef="auto",
+    target_entropy=-3,
+    verbose=1,
+    device="auto",
+)
+
+model.learn(total_timesteps=500_000)
+model.save("sac_carracing_features")
+
+# Testen (mit Rendern)
+test_env = CarRacing(render_mode="human")
+obs, _ = test_env.reset()
+done = False
+trunc = False
+while True:
+    action, _ = model.predict(obs, deterministic=True)
+    obs, r, done, trunc, _ = test_env.step(action)
+    test_env.render()
+    if done or trunc:
+        obs, _ = test_env.reset()