Update

README.md

@@ -1,8 +1,8 @@
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 title: RL Interpretable Policy Via Kolmogorov Arnold Network
-emoji: 👀
-colorFrom: green
-colorTo: gray
+emoji: 🧠➡️🔢
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+colorTo: violet
 sdk: gradio
 sdk_version: 4.29.0
 app_file: app.py

app.py

@@ -34,6 +34,8 @@ In this demo, we showcase a method to make a trained Reinforcement Learning (RL)
 
 For more information about KAN you can read the [paper](https://arxiv.org/abs/2404.19756), and check the [PyTorch official information](https://github.com/KindXiaoming/pykan).
 To follow the progress of KAN in RL you can check the repo [kanrl](https://github.com/riiswa/kanrl).
+
+[![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"]