Try to repair Mujoco

app.py

@@ -38,7 +38,7 @@ To follow the progress of KAN in RL you can check the repo [kanrl](https://githu
 [![riiswa/kanrl - GitHub](https://gh-card.dev/repos/riiswa/kanrl.svg)](https://github.com/riiswa/kanrl)
 """
 
-envs = ["CartPole-v1", "MountainCar-v0", "Acrobot-v1", "Pendulum-v1", "MountainCarContinuous-v0", "LunarLander-v2", "Swimmer-v3", "Hopper-v3"]
+envs = ["CartPole-v1", "MountainCar-v0", "Acrobot-v1", "Pendulum-v1", "MountainCarContinuous-v0", "LunarLander-v2", "Swimmer-v3", "Hopper-v3", "HalfCheetah-v3", "Walker2d-v3"]
 
 
 if __name__ == "__main__":
@@ -46,10 +46,11 @@ if __name__ == "__main__":
 
     def load_video_and_dataset(_env_name):
         env_name = _env_name
+        agent = "ppo"
+        if env_name == "Swimmer-v3" or env_name == "Walker2d-v3":
+            agent ="trpo"
 
-        if env_name.startswith("Swimmer") or env_name.startswith("Hopper-v3"):
-            gr.Warning("We're currently in the process of adding support for Mujoco environments, so the application may encounter crashes during this phase. We encourage contributors to join us in the repository https://github.com/riiswa/kanrl to assist in the development and support of other environments. Your contributions are invaluable in ensuring a robust and comprehensive framework.")
-        dataset_path, video_path = generate_dataset_from_expert("ppo", _env_name, 15, 3)
+        dataset_path, video_path = generate_dataset_from_expert(agent, _env_name, 15, 3)
         return video_path, gr.Button("Compute the symbolic policy!", interactive=True), {
             "dataset_path": dataset_path,
             "ipe": None,
@@ -126,7 +127,7 @@ if __name__ == "__main__":
 
         with gr.Row():
             with gr.Column():
-                gr.Markdown("### Pretrained policy loading (PPO from [rl-baselines3-zoo](https://github.com/DLR-RM/rl-baselines3-zoo))")
+                gr.Markdown("### Pretrained policy loading (PPO or TRPO from [rl-baselines3-zoo](https://github.com/DLR-RM/rl-baselines3-zoo))")
                 choice = gr.Dropdown(envs, label="Environment name")
                 expert_video = gr.Video(label="Expert policy video", interactive=False, autoplay=True)
                 kan_widths = gr.Textbox(value="2", label="Widths of the hidden layers of the KAN, separated by commas (e.g. `3,3`). Leave empty if there are no hidden layers.")