useOfAi

RL Testing/lev_PPO.ipynb

@@ -293,7 +293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "7ee8fb34",
    "metadata": {},
    "outputs": [
@@ -333,6 +333,7 @@
     }
    ],
    "source": [
+    "# The following was generated by AI - see [19]\n",
     "environ = LevPodEnv(use_gui=False, initial_gap_mm=14, max_steps=500)  # Start below target\n",
     "model = ActorCriticNetwork(environ.observation_space.shape[0], environ.action_space.shape[0]).to(device)\n",
     "train_data, reward, gap_error = rollout(model, environ)\n",
@@ -380,7 +381,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "e6f27ed4",
    "metadata": {},
    "outputs": [
@@ -415,6 +416,7 @@
     }
    ],
    "source": [
+    "# The following was generated by AI - see [20]\n",
     "# Visualize the new reward function\n",
     "gap_errors_mm = np.linspace(0, 20, 100)\n",
     "gap_rewards = np.exp(-0.5 * (gap_errors_mm / 3.0)**2)\n",
@@ -443,7 +445,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "fb554183",
    "metadata": {},
    "outputs": [
@@ -457,6 +459,7 @@
     }
    ],
    "source": [
+    "# The following was generated by AI - see [21]\n",
     "import os\n",
     "from datetime import datetime\n",
     "\n",
@@ -701,7 +704,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "3678193c",
    "metadata": {},
    "outputs": [