Update README.md

README.md

@@ -1,74 +1,76 @@
----
-library_name: hivex
-original_train_name: AerialWildfireSuppression_difficulty_10_task_2_run_id_1_train
-tags:
-- hivex
-- hivex-aerial-wildfire-suppression
-- reinforcement-learning
-- multi-agent-reinforcement-learning
-model-index:
-- name: hivex-AWS-PPO-baseline-task-2-difficulty-10
-  results:
-  - task:
-      type: sub-task
-      name: maximize_preparing_non_burning_trees
-      task-id: 2
-      difficulty-id: 10
-    dataset:
-      name: hivex-aerial-wildfire-suppression
-      type: hivex-aerial-wildfire-suppression
-    metrics:
-    - type: crash_count
-      value: 0.15833333730697632 +/- 0.20572934499076767
-      name: Crash Count
-      verified: true
-    - type: extinguishing_trees
-      value: 19.241666620969774 +/- 33.273080342427235
-      name: Extinguishing Trees
-      verified: true
-    - type: extinguishing_trees_reward
-      value: 96.20833342075348 +/- 166.36540223877446
-      name: Extinguishing Trees Reward
-      verified: true
-    - type: fire_out
-      value: 0.20833333507180213 +/- 0.32387908421054906
-      name: Fire Out
-      verified: true
-    - type: fire_too_close_to_city
-      value: 0.95 +/- 0.22360679774997894
-      name: Fire too Close to City
-      verified: true
-    - type: preparing_trees
-      value: 995.8083220481873 +/- 896.6925434987216
-      name: Preparing Trees
-      verified: true
-    - type: preparing_trees_reward
-      value: 4979.041623306274 +/- 4483.462788982591
-      name: Preparing Trees Reward
-      verified: true
-    - type: water_drop
-      value: 36.908333444595335 +/- 20.718840949931526
-      name: Water Drop
-      verified: true
-    - type: water_pickup
-      value: 36.41666669845581 +/- 20.746415247545407
-      name: Water Pickup
-      verified: true
-    - type: cumulative_reward
-      value: 5726.971720504761 +/- 3142.936334111313
-      name: Cumulative Reward
-      verified: true
----
-
-This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>2</code> with difficulty <code>10</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>
-
-Environment: **Aerial Wildfire Suppression**<br>
-Task: <code>2</code><br>
-Difficulty: <code>10</code><br>
-Algorithm: <code>PPO</code><br>
-Episode Length: <code>3000</code><br>
-Training <code>max_steps</code>: <code>1800000</code><br>
-Testing <code>max_steps</code>: <code>180000</code><br><br>
-
-Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>
-Download the [Environment](https://github.com/hivex-research/hivex-environments)
+---
+library_name: hivex
+original_train_name: AerialWildfireSuppression_difficulty_10_task_2_run_id_1_train
+tags:
+- hivex
+- hivex-aerial-wildfire-suppression
+- reinforcement-learning
+- multi-agent-reinforcement-learning
+model-index:
+- name: hivex-AWS-PPO-baseline-task-2-difficulty-10
+  results:
+  - task:
+      type: sub-task
+      name: maximize_preparing_non_burning_trees
+      task-id: 2
+      difficulty-id: 10
+    dataset:
+      name: hivex-aerial-wildfire-suppression
+      type: hivex-aerial-wildfire-suppression
+    metrics:
+    - type: crash_count
+      value: 0.15833333730697632 +/- 0.20572934499076767
+      name: Crash Count
+      verified: true
+    - type: extinguishing_trees
+      value: 19.241666620969774 +/- 33.273080342427235
+      name: Extinguishing Trees
+      verified: true
+    - type: extinguishing_trees_reward
+      value: 96.20833342075348 +/- 166.36540223877446
+      name: Extinguishing Trees Reward
+      verified: true
+    - type: fire_out
+      value: 0.20833333507180213 +/- 0.32387908421054906
+      name: Fire Out
+      verified: true
+    - type: fire_too_close_to_city
+      value: 0.95 +/- 0.22360679774997894
+      name: Fire too Close to City
+      verified: true
+    - type: preparing_trees
+      value: 995.8083220481873 +/- 896.6925434987216
+      name: Preparing Trees
+      verified: true
+    - type: preparing_trees_reward
+      value: 4979.041623306274 +/- 4483.462788982591
+      name: Preparing Trees Reward
+      verified: true
+    - type: water_drop
+      value: 36.908333444595335 +/- 20.718840949931526
+      name: Water Drop
+      verified: true
+    - type: water_pickup
+      value: 36.41666669845581 +/- 20.746415247545407
+      name: Water Pickup
+      verified: true
+    - type: cumulative_reward
+      value: 5726.971720504761 +/- 3142.936334111313
+      name: Cumulative Reward
+      verified: true
+---
+
+This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>2</code> with difficulty <code>10</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>
+
+Environment: **Aerial Wildfire Suppression**<br>
+Task: <code>2</code><br>
+Difficulty: <code>10</code><br>
+Algorithm: <code>PPO</code><br>
+Episode Length: <code>3000</code><br>
+Training <code>max_steps</code>: <code>1800000</code><br>
+Testing <code>max_steps</code>: <code>180000</code><br><br>
+
+Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>
+Download the [Environment](https://github.com/hivex-research/hivex-environments)
+
+[hivex-paper]: https://arxiv.org/abs/2501.04180